## I. INTRODUCTION Family enterprises in Morocco operate in a culturally rich and emotionally charged environment, where familial and societal values intertwine. The intricate interplay of emotions within these businesses goes beyond individual sentiments, forming a collective experience woven into the operational fabric (Castro and Aguilera 2014). Because, the cultural context of Morocco is marked by distinct characteristics such as collectivism, high power distance, and diversity. These cultural attributes contribute to the complexity of understanding socio- emotional wealth (SEW) within the business landscape of Morocco. The emphasis on collectivism implies a societal orientation towards group cohesion and interdependence, potentially influencing how SEW is perceived and managed within family businesses (Faccio and Lang 2002). Additionally, the high power distance prevalent in Moroccan culture, reflecting a hierarchical structure and acceptance of authority, may impact the dynamics of socio-emotional wealth in business contexts. Furthermore, the cultural diversity inherent in Morocco introduces a rich tapestry of perspectives and experiences, adding layers to the intricacies of socio-emotional wealth within the business domain. Exploring how emotions interact with the ambiguity of change in this cultural context becomes particularly interesting, as it involves navigating the intersections of collective values, power dynamics, and diverse perspectives in the realm of family businesses in Morocco. Furthermore, in addition to the cultural aspects characterizing Moroccan family businesses, an additional layer of complexity can be discerned. Firstly, family enterprises inherently strive to preserve their status quo, deeply rooted in established identities and family names. This inclination, while fostering a sense of continuity, may also render them susceptible to forgoing opportunities for growth (Gómez-Mejía et al., 2007). The commitment to maintaining traditional structures and practices could inadvertently hinder the pursuit of innovative avenues. Secondly, the concept of ambidexterity gains significance in understanding how these family firms navigate the delicate balance between preserving established practices that have proven successful and exploring potential avenues for growth. Achieving ambidexterity becomes a critical challenge for family businesses, as it requires a nuanced approach to simultaneously uphold what works effectively and explore new possibilities without jeopardizing their overall performance (Poutziouris et al. 2006). This research investigates the intricate interplay of socio-emotional wealth (SEW) and its crucial role in facilitating ambidexterity within family firms when confronted with transformative change. It aims to elucidate how these entities not only manage to uphold their traditional identity, values, and established business models but also skillfully navigate and explore change (Chrisman, Chua, & Steier, 2005). The study examines the mechanisms through which socio-emotional wealth serves as a strategic facilitator, enabling family firms to delicately balance the preservation of ingrained elements contributing to their historical success and the proactive exploration of innovative avenues for sustained growth. This exploration goes beyond mere survival strategies, emphasizing the serene and strategic handling of change. By analyzing the complex relationship between socio-emotional wealth and the ambidextrous responses of family firms, the research seeks to contribute nuanced insights to the evolving discourse on strategic adaptability and resilience within the familial business context (Colquitt & Zapata-Phelan, 2007). ## II. LITTERTURE REVIEW ### a) Family Firms Socio Emotional Wealth The evolution of research paradigms in family businesses has shifted from a cognitive emphasis to a recognition of the crucial role of emotions. The Socio-Emotional Wealth (SEW) paradigm offers an alternative approach, focusing on the affective and social aspects of management, overcoming the limitations of cognitive paradigms. By adopting the SEW paradigm, researchers gain a comprehensive understanding of the intricate interactions among family members, emphasizing the emotional and social dimensions inherent in family dynamics. This multidisciplinary approach integrates cognitive and socio-emotional dimensions, addressing specific challenges faced by family businesses, including interpersonal conflicts, family member management, and succession planning (Schulze & Gedajlovic, 2010). The development of the Socio-Emotional Wealth (SEW) concept is rooted in antecedents like "familiness," family values, and familial leadership. Familiness, encompassing loyalty and cooperation, provides emotional security among family business members. Positive familial leadership reinforces these values, contributing to talent retention, organizational resilience, and overall business performance. Recognizing and cultivating these antecedents is crucial for fostering the development of socio-emotional wealth, ensuring the sustainability of family businesses (Sharma, al 2004). SEW originated from research emphasizing emotional and social dimensions in managing family businesses, shifting the focus from organizational structure to the family system of operation during leadership transitions. SEW influences both financial and non-financial performance, requiring consideration of family relationships, emotions, values, and norms to understand family business dynamics. Recent examinations of SEW in challenges like succession management and family conflicts highlight its crucial role. However, effective management is essential to prevent SEW from shifting from an asset to a burden (Ucbasaran et al., 2001). Diverse definitions of SEW underscore its complexity. Some highlight the importance of family relationships, while others emphasize non-financial priorities distinguishing family businesses. Regardless, they agree on the existence of various priorities linked to socio-emotional dimensions like family values, norms, traditions, and relationships. These considerations contribute to the distinct behavior of family businesses compared to capitalist counterparts (Busenitz et al., 2003). The priorities of family businesses vary, influenced by different generations or family members involved in management. These socio-emotional priorities lead to unique strategic choices, impacting both financial and non-financial performance. Understanding these priorities is crucial for com-prehending the dynamics of family businesses and their strategic management. When it comes to measuring socio-emotional wealth (SEW) in family businesses, indirect proxies like ownership structure and control duration are commonly used. However, these proxies have limitations, as they may not fully capture the complexity of SEW, and their associations can vary based on context and cultural factors. Critics argue that specific behaviors attributed to SEW may be influenced by factors beyond it, challenging the establishment of a direct connection. The lack of precision and the assumption of positive valence in emotional behaviors are significant drawbacks in using indirect indicators (Debicki et al., 2009). To address these limitations, there is a need for direct multidimensional measures to assess SEW more accurately. The Fiber model, created in 2012 by Gomez and Mejia, presents five dimensions (Fidelity, Identity, Belongingness, Engagement, and Responsibility), allowing for a nuanced and complex assessment of SEW in family businesses. This model enables a more comprehensive understanding of the emotional aspects and the heterogeneity of affective endowments within family-owned businesses. ## i. Family Control and Influence Family influence on enterprise strategy is twofold: direct leadership roles and oversight on the board. Rooted in family equity ownership, this influence prioritizes family control. This control motive can impact strategic and financial decisions, discouraging external partnerships to maintain control. Internal recruitment, especially of family members, fosters a culture of engagement and innovation, aligning with characteristics of small and medium-sized family enterprises. This approach, while limiting external expertise infusion, promotes a committed and familial environment, driving innovation and organizational cohesion (Hernández-Perlines et al., 2020). ## ii. Identification by the Company The study delves into the distinct identity formed by the intrinsic link between family and business in family enterprises. Family owners prioritize their business's reputation, viewing it as an extension of the family's identity. The conscious cultivation of this identity represents the second dimension of socio-emotional wealth. Family members grow up with a strong awareness of their affiliation, internalizing identity markers that become integral to their personal identity. The sense of belonging varies based on the dominant culture, emphasizing the need to consider cultural dimensions in studying family businesses and their unique identity (Makó et al., 2016). ## iii. Emotional Attachment The emotional dynamics within family businesses involve a delicate balance, navigating conflicts between family and business systems. Emotions, both positive and negative, impact management, governance, and strategy. Emotional costs, determined by rewards from emotional investments, influence family members' behaviors. Positive rewards reinforce supportive attitudes, while low rewards may lead to conflicts and selfishness. Culture, particularly in collectivist cultures like the UAE, plays a significant role in shaping emotions, emphasizing harmony and control over expressions. In essence, emotional costs and cultural influences shape the intricate emotional landscape of family businesses (Debicki et al., 2016). ## iv. Transgenerational Will Preserving the business for future generations is a primary focus in family enterprises, driven by socio-emotional wealth considerations. Upholding the dynasty and family values over generations guides the planning horizon, emphasizing multi-generational continuity. Family enterprises prioritize a long-term planning approach, valuing sustainable wealth creation and legacy building. The close ties between family and business contribute to this vision, fostering ethical management practices and a commitment to corporate social responsibility. In essence, the enduring goal of family enterprises is the preservation of family values and the business for successive generations (Gomez Mejia, et al., 2018). ## v. Binding Social Ties Maintaining stable relationships with stakeholders is crucial for the long-term success of family businesses. Personalizing connections enables a better understanding of stakeholders' needs, fostering adaptability. This approach, aligned with family culture and values, doesn't compromise business objectives but reinforces stakeholder loyalty. These enduring relationships prove beneficial during economic challenges, as stakeholders connected through personal ties are more likely to support struggling family businesses. In summary, stable relationships with stakeholders, rooted in family values, enhance adaptability, resilience, and long-term profitability for family businesses (Berrone et al., 2010). ### b) Organizational Capacity for Change & Organizational Ambidexterity Organizational capacity for change in family firms involves the ability to balance ambidexterity, which is the dual challenge of preserving established practices and exploring new opportunities for change. Ambidex terity in family firms encompasses the preservation of successful material and immaterial aspects such as values, identity, and other foundational elements, while also actively exploring and adapting to change (Wang et al. 2020). Preserving what works for family firms involves maintaining the material and immaterial aspects that contribute to their historical success. This preservation includes safeguarding tangible assets, effective business models, and established identities that are deeply rooted in family values. Immaterially, it involves nurturing and preserving socio-emotional wealth (SEW), which comprises emotional bonds, trust, and a sense of responsibility within the family and the organization (Bamford and Forrester 2003; Dunphy 1996). On the other hand, exploring change implies actively seeking and adapting to new opportunities for growth and development. This exploratory aspect of ambidexterity requires family firms to possess the organizational capacity for change. This capacity is influenced by socio-emotional wealth, which serves as a guiding principle and determinant in decision-making related to change (Herold et al. 2007). The socio-emotional wealth of family firms plays a crucial role in shaping their organizational capacity for change. Emotional attachment, relational synergy, and social capital, components of socio-emotional wealth, contribute to the family firm's ability to navigate ambidextrous challenges. Emotional attachment fosters commitment to preserving established elements, while relational synergy enhances collaboration and trust among family members and organizational actors. Social capital facilitates the establishment of a climate of trust, which is vital for effective change management (Rafferty and Simons 2006). Douglas and Thomas (2006) conducted a comprehensive study to measure OCC, identifying eight distinct dimensions encompassing human, organizational, cultural, and socio-emotional capabilities. Their meticulous process involved reviewing books and articles related to organizational change, providing a comprehensive understanding of OCC and its components. Trustworthy leadership involves the capability of senior executives to garner the trust of organizational members and guide them toward achieving collective goals. Trusted followership refers to the competence of non-executive employees to engage in constructive dissent and/or willingly embrace a new direction advocated by senior executives. Capable champions signify an organization's ability to attract, retain, and empower change leaders to evolve and emerge (Judge and Blocker (2008). Involved mid-management denotes the skill of middle managers to effectively establish connections between senior executives and other members of the organization. Innovative culture embodies the organization's capacity to establish norms of innovation and promote innovative activities (Stevens 2013). Accountable culture reflects the organization's ability to carefully steward resources and successfully meet pre-determined deadlines (Vakola 2013). Effective communication underscores the organization's proficiency in communicating vertically, horizontally, and with customers (Stensaker 2014). System thinking signifies the organization's ability to focus on root causes and recognize the interdependencies within and outside the organizational boundaries (Heckmann et al. 2016). Table: Research hypotheses <table><tr><td>Hypotheses</td><td>Description</td><td>Source</td></tr><tr><td>H1</td><td>Socio-emotional Wealth has an impact on Organizational Change Capability.</td><td></td></tr><tr><td>H2</td><td>There is a significant relationship between Socio-emotional Wealth (RSE) and Organizational Change Capability (OCC).</td><td></td></tr><tr><td>H3</td><td>Emotional attachment has a positive effect on establishing climate of trust during the change period.</td><td>(Kimberly A. Eddleston, 2010).</td></tr><tr><td>H4</td><td>The relational synergy among family members positively influences the process of selecting change champions.</td><td>(Nava Michael, 2013).</td></tr><tr><td>H5</td><td>Family firmness has a positive effect on the selection of chang champions during the change period</td><td>Ibrahim Sonfani and Lam (2001).</td></tr><tr><td>H6</td><td>Family firmness has a positive effect on establishing a culture of innovation within the organization.</td><td>Sciaccia et al. (2015)</td></tr><tr><td>H7</td><td>The sense of identification with the company positively influences the sense of responsibility of the various actors involved in the context of change</td><td>Gregory J. Dardis (2006).</td></tr></table> ### c) Material & Methode ## i. Organizational Context This study was conducted within a Moroccan SME family business operating in the recycling sector, characterized by its industrial focus. During the research period, the organization was in the midst of a comprehensive organizational change initiative. The ongoing transformation involved substantial resource rationalization, restructuring efforts, and a strategic realignment of services. Significant alterations were implemented, encompassing asset disposals, the closure of multiple offices, restructuring of education delivery mechanisms, a reduction in management and administrative positions, the introduction of a program-based organizational structure, and an overall reduction in staff numbers. These changes had far-reaching implications for most members of the staff, reflecting a scenario where the majority of individuals were affected to varying extents by the organizational transformation. ## ii. Research Design The mixed-methods research design employed in this study integrated both qualitative and quantitative research approaches to provide a comprehensive understanding of the research question. The qualitative component was instrumental in capturing non-numerical data through methods such as interviews and open-ended surveys. This approach was chosen to delve deeply into the nuances of the theoretical constructs within the specific context of Morocco. By using qualitative methods, the study aimed to explore and validate the theoretical framework, ensuring its relevance and applicability to the unique cultural and organizational dynamics of Moroccan family firms. Following the qualitative exploration, the research seamlessly transitioned into the quantitative phase to empirically test the hypothetical relationships established in the conceptual models. The quantitative component involved the collection and analysis of numerical data, allowing for statistical examination of the proposed hypotheses. Surveys, structured interviews, or structured observations may have been employed to gather quantitative data on variables related to SEW, ambidexterity, and organizational capacity for change. The sequential nature of the research design, with qualitative exploration preceding quantitative analysis, enabled a holistic and in-depth investigation. This mixed-methods approach not only provided a nuanced understanding of the underlying mechanisms but also allowed for the validation and generalization of findings, contributing to a robust and comprehensive research outcome. ### d) Exploratory Qualitative Study This research employs a mixed-methods approach, combining exploratory research and case study analysis. The initial phase involves exploratory research, allowing for a preliminary investigation of the phenomenon. Following Masmoudin's (2007) recommendation, this approach situates the research within its authentic production context. The aim is to produce knowledge that extends beyond specific instances, providing a comprehensive understanding. Moreover, the exploratory research phase seeks precision in information, addressing common critiques of neglecting contextual elements in management sciences. This phase delves into the real-world context of the phenomenon, offering insights into its authentic production setting. ## i. Sample Subsequently, the research transitions to a detailed analysis of three case studies, meticulously selected based on stringent criteria. These criteria include theoretical representativeness, variety, balance, and discovery potential. Theoretical representativeness ensures that the chosen cases faithfully depict the studied phenomenon, contributing to theoretical enrichment. Variety in case selection is paramount, as significant differences in key characteristics facilitate thorough comparative analysis. Striking a balance between commonalities and specificities among selected cases is essential for a holistic understanding. This ensures that the analysis captures both overarching patterns and unique aspects. The methodology aims to provide a nuanced and comprehensive exploration of the targeted phenomenon, offering both generalizable insights and detailed, context-rich information. Through this mixed-methods approach, the research endeavors to contribute significantly to the existing body of knowledge. ## ii. Data Source Once the study population was rigorously defined, individual interviews with an average duration of 1 hour and 5 minutes were conducted to deepen our understanding of leadership dynamics within family SMEs. The interview guide comprised two types of questions. Firstly, open-ended questions were used to allow participants to freely express their experiences and opinions, capturing the complex and rich reality of the study subject. In contrast, closed binary questions were employed to obtain specific responses, providing clear indications on particular aspects of the research themes and facilitating comparisons between participants. Control queries were also used to validate participant responses and ensure a high level of objectivity in the study. All interviews were recorded with a digital voice recorder to ensure accurate and detailed transcription of the exchanges, preserving data integrity for subsequent analyses. Alongside audio recordings, written notes were taken to complement recordings with additional observations or important nuances that may not be captured solely by voice recordings. A specific interview guide, aligned with research objectives and themes, provided a clear and consistent structure while allowing the necessary flexibility to explore each participant's unique perspectives. An explanatory note, included in the appendix, offered additional context and study objectives to facilitate participant understanding. ## iii. Data Analysis Following the completion and recording of interviews with the target sample, the subsequent step in our research was the analysis of the gathered data. In the realm of qualitative methodology, we opted for content analysis, a method that systematically transcribes, codes, and categorizes emerging themes and concepts from the interview recordings. This approach allowed for an in-depth exploration of participants' discourses and experiences, capturing the complexity and uniqueness of the studied phenomena within their specific contexts. The retrograde analytical approach, involving iterative movements between analysis phases, enriched our understanding by accommodating the diversity and depth of the collected data. Ultimately, this method enhanced the robustness of our results, providing a nuanced perspective on the leadership dynamics within family SMEs. ### e) Confirmatory Quantitative Study The quantitative methodology in this thesis aims to enhance and deepen the insights gained from the qualitative contextualization phase. The quantitative methodology in this thesis plays a pivotal role, particularly in the application of Structural Equation Modeling (SEM). Through a two-step approach, it leverages the insights gained from the qualitative study to enhance the understanding of the research problem. The initial qualitative phase refines hypotheses and validates variables within the conceptual model. Subsequently, the quantitative study, utilizing SEM, systematically tests these hypotheses. This approach involves collecting data from a broad executive population within family-owned SMEs. The quantifiable data obtained facilitates a nuanced analysis of the relationships between variables, offering specific and statistically validated insights into the researched phenomenon. The use of SEM allows for a sophisticated examination of complex relationships, contributing to a more robust and comprehensive understanding of the dynamics within these organizations. #### Sample The application of Structural Equation Modeling (SEM) is widely regarded by experts as contingent upon a substantial sample size, with the prevailing sentiment being "The bigger, the better." The rationale behind this perspective lies in the belief that a larger sample ensures greater precision in statistical estimations, particularly concerning standard errors. Despite numerous studies attempting to pinpoint an appropriate minimum sample size, a consensus on what qualifies as "sufficiently large" remains elusive. Empirical orthodoxy suggests a minimum threshold of 150, with some authors even advocating against the publication of SEM analyses based on samples fewer than 150. However, Iacobucci (2010) challenges this conventional wisdom, contending that, under specific conditions, such as a reliable measurement scale, a modest sample size of 50 or 100 may prove adequate for structurally uncomplicated models. Moreover, alternative recommendations propose that the determination of the optimal sample size is contingent upon factors such as the number of variables employed (Bentler and Chou, 1987) or the magnitude of their weights (Mac Callum et al., 2006). Models featuring a substantial number of parameters to estimate are suggested to necessitate larger samples. The common method for determining sample size in SEM involves the ratio of observations per parameter (Kline, 2011). Regarding our research, we have chosen a sample of 200 respondents from 20 family-owned SMEs located in the Greater Casablanca region. This decision was guided, as presented in the sampling section, by criteria of homogeneity, statistical representativeness, variety, and relevance. Below is a summary table of the sampling process. The rationale behind the selection of our 200-sample cohort was strategically guided by several criteria. First and foremost, our focus extended to all SMEs situated in Casablanca, emphasizing their significance within the industrial sector. Additionally, we considered the active involvement of both the first and second generations in the management of these enterprises. Relevance played a pivotal role in our selection process, with a particular emphasis on the multitude of organizational change projects undertaken by the chosen SMEs. This ensured that our sample was not only diverse but also reflective of the dynamic nature of business environments. Variety was another critical aspect taken into account, encompassing the diversity of core business activities among the selected SMEs and varying types of family ownership structures. Through these carefully considered criteria, our aim was to construct a representative and pertinent sample that aligns with the principles of homogeneity, relevance, and variety in the context of our research. #### Data Source We utilized a questionnaire as the primary data collection tool in our quantitative study due to its effectiveness in handling large samples, conducting statistical tests, and enabling numerical comparisons. The questionnaire, defined as a direct inquiry tool with pre-qualified closed-ended questions, facilitated participant engagement. Constructing the questionnaire involved selecting specific measurement scales tailored to our research context. The choice between using existing validated scales or creating context-specific scales depended on their relevance and validity for our research problem. The crucial step of item selection, composing the questions for data collection, was guided by the literature review, conceptual model, and research objectives. Each item was meticulously designed to be clear, understandable, and relevant to measure the studied variables. The questionnaire construction process involved a systematic approach, incorporating appropriate measurement scales and relevant item selection based on literature, conceptual framework, and research goals, ensuring the quality and relevance of the questions posed. We employed a Likert-scale-based questionnaire as the primary data collection tool in our quantitative study due to its efficiency in managing extensive samples, conducting statistical analyses, and facilitating numerical comparisons. The Likert scale, widely recognized for its versatility, allowed participants to express their opinions on a range of items through a structured response format. Constructing the questionnaire involved selecting specific Likert scale measures tailored to our research context. The Likert scale's ordinal nature enabled participants to provide nuanced responses, offering a more detailed understanding of their perspectives. A "stratified sampling" method was chosen to ensure comprehensive representation of the diverse population under study, which encompasses different hierarchical levels and family/non-family members. This approach aligns with the population's heterogeneity, where an exhaustive list of individuals is available, and statistical representativity is crucial for result validity. The chosen sample size was determined considering the Structural Equation Modeling (SEM) analysis planned for the study. Anticipating both basic analyses and factor analysis, we aimed for a sample size exceeding the minimum criterion set by some researchers (e.g., over 30 observations or four to five times the number of variables), establishing a target of 200 respondents. In the context of our survey, we employed a technique that allowed us to collect data without any missing cases. Specifically, a forced-response option was set for each item in the Google questionnaire, compelling participants to respond to all survey items. If participants attempted to navigate to the next page without answering all the elements, they received a warning message instructing them to complete all items before proceeding. Given the conditions and normality characteristics of the collected data in the context of our survey, the maximum likelihood (ML) method was chosen as the estimation technique for this study. #### Method of Analysis In the context of this study, the decision was made to employ Structural Equation Modeling (SEM) as the analytical method. This choice stems from several factors, notably aligned with the thesis objectives, which involve testing hypotheses and examining the relationship between socioemotional wealth and organizational capacity for change. Additionally, the inherent advantages of the Structural Equation Modeling method were taken into consideration. LISREL was selected as the analytical tool due to its extensive history, established reputation, and analytical prowess in the domain of linear structural equations. Its user-friendly interface and advanced functionalities facilitated the estimation of parameters within the conceptual model, assessment of data fit to the model, hypothesis testing, and generation of significant results for our research. ## III. RESEARCH RESULTS ### Exploratory Factor Analysis (EFA) To determine the appropriateness of Exploratory Factor Analysis (EFA), it is necessary for all variables to be standardized. To achieve this, the Kaiser-Meyer-Olkin (KMO) and Bartlett's test of sphericity were employed. The general rule is that the KMO Index ranges from 0 to 1. Kaiser (1974) recommends that a KMO value higher than 0.5 is acceptable, but he categorizes values between 0.5 and 0.7 as mediocre, values between 0.7 and 0.8 as good, values between 0.8 and 0.9 as excellent, and values exceeding 0.9 as superb. In our case, the KMO result obtained after testing the 36 items is 0.88, falling within the range of being considered good. This indicates the appropriateness of the factor analysis (see table1). Bartlett's test of sphericity is another tool used to verify the feasibility of factor analysis. The Bartlett test assesses the null hypothesis that the original correlation matrix is the identity matrix. For factor analysis to be appropriate, this test should be significant, with a significance value below 0.05. As shown in the table, we obtained a highly significant Bartlett's sphericity value ( $p =.000 < 0.05$ ), confirming the suitability of factor analysis. Table 1: Exploratory Factor Analysis Indicators <table><tr><td colspan="2">Kaiser-Meyer-Olkin Sampling Adequacy Measure</td><td>,882</td></tr><tr><td>Bartlett&#x27;s Sphericity Test</td><td>Approximate Chi-Square</td><td>1125,701</td></tr><tr><td></td><td>Ddl</td><td>66</td></tr><tr><td></td><td>Bartlett&#x27;s Significance</td><td>,000</td></tr><tr><td>Cronbach&#x27;s Alpha</td><td>,865</td><td></td></tr><tr><td></td><td>Variables number</td><td>12</td></tr><tr><td></td><td></td><td>)</td></tr></table> Furthermore, the overall reliability test, represented by Cronbach's Alpha, follows the basic guideline proposed by George and Mallery (2003). It suggests that internal consistency among item values is maintained when the alpha coefficient exceeds 0.7. In our case, we achieved an indicator of 0.85 calculated based on items and 0.86 calculated based on variables, both indicating excellent results and suggesting the perfect reliability of latent factors. Regarding the quality of item representation, as confirmed by the table 2, the indices we utilized exhibit strong quality, ranging from a lower value (Identification $= 0.31$ ) to a higher value (Intergenerational Willingness $= 0.66$ ). Items related to six variables possess values exceeding 0.5 ( $n > 0.5$ ), notably: Emotional Attachment $= 0.66$; Familiarity $= 0.52$; Intergenerational Willingness $= 0.69$; Trust $= 0.54$; Empowerment $= 0.55$; Change Champion $= 0.59$. The remaining items are confined to a range between 3 and 4. The correlation matrix is used to verify item coherence and consistency. The basic rule suggests eliminating items with values below 0.2. In our case, after extracting the correlation matrix, we observed strong correlations among items measuring socio-emotional wealth. For example, Emotional Attachment and Familiness = 0.64; Emotional Attachment and Transgenerational Willingness = 0.68; Relational Synergy and Transgenerational Willingness = 0.49. Similar correlations were found among items measuring organizational change capacity: Trust and Communication = 0.52; Empowerment and Change Champion = 0.53; Change Champion and Communication = 0.55. No removal of items is necessary. Table 2: Quality of Representation of Items <table><tr><td></td><td>Emotional Attachment</td><td>Relational Synergy</td><td>Familiness</td><td>Intergenerational Willingness</td><td>Ownership and Control</td><td>Firm Identification</td></tr><tr><td rowspan="2">Initial</td><td>0,664</td><td>0,449</td><td>0,528</td><td>0,69</td><td>0,378</td><td>0,17</td></tr><tr><td>0,643</td><td>0,435</td><td>0,519</td><td>0,615</td><td>0,397</td><td>0,145</td></tr><tr><td>Extraction</td><td>Trust</td><td>Communication</td><td>Responsibility culture</td><td>Systemic Thinking</td><td>Change Champion</td><td>Innovation Culture</td></tr><tr><td>Initial</td><td>0,548</td><td>0,475</td><td>0,554</td><td>0,437</td><td>0,596</td><td>0,415</td></tr><tr><td>Extraction</td><td>0,534</td><td>0,483</td><td>0,562</td><td>0,577</td><td>0,59</td><td>0,374</td></tr></table> The second matrix presented is the structure matrix, reflecting the factorial weight of different items. The main rule is that all values should exceed 0.5 (n > 0.5). The result based on our research data (see table) confirms that all our items have explanatory weights above the norm, with a minimum value of (Identification by the company = 0.5) and a maximum value of (Emotional Attachment = 0.77). Moreover, more than six items surpass this threshold, such as Emotional Attachment = 0.774; Familiness = 0.721; Intergenerational Willingness = 0.63; Ownership and Control = 0.62; Trust = 0.723; Communication = 0.665; Responsibility = 0.74; Change Champion = 0.76; Innovation Culture = 0.611. To determine the number of explanatory factors, we opted for graphical analysis of eigenvalues. The rule is that each eigenvalue should be strictly greater than 1.0 (Fabrigar et al., 1999; Kline, 2013). The eigenvalue graph based on initial factors, presented in the figure below, allowed us to observe that after the third factor, the line is almost flat, indicating that these factors have eigenvalues strictly greater than 1.0. Additionally, the first two factors explain approximately $52\%$ of the information extracted from the model. In summary, through Exploratory Factor Analysis (EFA), we were able to confirm that our model and the established causal and covariance links between different variables (Manifest, Latent) are coherent, valid, and reliable, as indicated by various indicators (Cronbach's Alpha = 0.86, Bartlett's Sphericity Test = 00, Kaiser-Meyer-Olkin = 0.88, structure matrix, factor matrix). This implies that the theoretical hypothetical relationship presumed in our research is true, i.e., (H1: there is a relationship between organizational capacity to change and socio-emotional wealth). Furthermore, using the correlation matrix and its indicators (Correlation Determinant = 0.03; and Average Correlation = 0.41), we were able to validate the significance of the relationship between the two theoretical constructs (H2: there is a significant relationship between socio-emotional wealth and organizational capacity to change). ### a) Confirmatory Factor Analysis The measurement model -Reliability and validity The structural equation modeling (SEM) analysis was conducted to assess the measurement model's fit for socio-emotional wealth (SEW) and organizational capacity for change. The goodness-of-fit indicators, including RMSEA (Root Mean Square Error of Approximation), IFI (Incremental Fit Index), CFI (Comparative Fit Index), and NNFI (Non-Normed Fit Index), were employed to evaluate the model's overall appropriateness. The results of the fit indicators demonstrated a well-fitting model, substantiating the reliability and validity of the measurement model for both socio-emotional wealth and organizational capacity for change. Table 3: Reliability of the Measurement Model <table><tr><td colspan="3">Indicators</td></tr><tr><td colspan="3">Socio-emotional wealth</td></tr><tr><td>x Factor Loading</td><td>Composite Reliability</td><td>Average Variance Extracted</td></tr><tr><td>,654</td><td>0.58</td><td>0.80</td></tr><tr><td colspan="3">Organizational Change Capability</td></tr><tr><td>,732</td><td>0,62</td><td>0.82</td></tr></table> The hypothesis testing aimed to confirm the proposed relationships between socio-emotional wealth and organizational capacity for change. H1 posited the existence of a relationship between these two constructs. The analysis provided empirical support for H1, indicating a statistically significant relationship between socio-emotional wealth and organizational capacity for change. The strength and direction of this relationship were further explored through factor loadings and path coefficients, affirming that variations in socio-emotional wealth were associated with changes in organizational capacity. H2, which suggested that this relationship is judged to be significant, was also confirmed by the SEM analysis. The statistical significance of the relationship was determined through p-values associated with the path coefficients. The p-values below the predetermined significance threshold (e.g., 0.05) provided evidence that the relationship between socio-emotional wealth and organizational capacity for change was not due to chance but indeed a meaningful and significant association. In conclusion, the SEM analysis substantiated the validity and reliability of the measurement model for socio-emotional wealth and organizational capacity for change. The confirmed relationship between these constructs supports both H1 and H2, providing empirical evidence that variations in socio- emotional wealth significantly influence organizational capacity for change in the context under investigation. These findings contribute to a deeper understanding of the dynamics between socio- emotional wealth and organizational change, emphasizing their meaningful and statistically significant connection. Table 4: Presentation of adjustment indices- measurement model <table><tr><td>Index</td><td>(RAMSEA)</td><td>IncrementalFit Index (IFI)</td><td>ComparativeFit Index (CFI)</td><td>Non-NormedFitIndex (NNFI)</td><td>Goodness ofFit Index (GFI)</td><td>Adjusted Goodness ofFit Index (AGFI)</td><td>NormalizedFit Index (NFI)</td></tr><tr><td>Results</td><td>0.08</td><td>0.95</td><td>0.95</td><td>0.95</td><td>0.96</td><td>0.90</td><td>0.94</td></tr><tr><td>Rule</td><td>≤ 0.06 ~ 0.08</td><td>≥0.90</td><td>≥0.95</td><td>≥0.90</td><td>≥0.90</td><td>intervalle [0, 1]</td><td>≥0.90</td></tr></table> ### b) Structural Model In order to test the hypotheses developed initially based on the theoretical framework and contextualization study, it is necessary to transform the measurement model into a structural model that represents the hypothetical relationships. This transition involves three steps: firstly, the removal of latent variables; secondly, the creation of causality links representing the hypotheses; and thirdly, the specification of endogenous and exogenous variables (Fornel, 1989). Three major conclusions have been drawn from the analysis of the structural model. Firstly, three out of five hypotheses have been validated—specifically, H3, H4, and H6 were accepted. However, H5 and H7 were rejected due to their low coefficients (H5: Familiness has a positive effect on the selection of change champions during the change period, $\beta = 0.19$; H7: The identification with the company positively influences the sense of responsibility of various actors involved in the change context, $\beta = 0.17$ ) (see the table below). Table 5: Reliability of the structural model <table><tr><td colspan="3">Indicators</td></tr><tr><td colspan="3">Socio-emotional wealth</td></tr><tr><td>x Factor Loading</td><td>Composite Reliability</td><td>Average Variance Extracted</td></tr><tr><td>,754</td><td>0.75</td><td>0.80</td></tr><tr><td colspan="3">Organizational Change Capability</td></tr><tr><td>,642</td><td>0,65</td><td>0.82</td></tr></table> Table 6: Presentation of adjustment indices- Structural model <table><tr><td>Indice</td><td>(RAMSEA)</td><td>Incremental Fit Index (IFI)</td><td>Comparative Fit Index (CFI)</td><td>Non-Normed Fit Index (NNFI)</td><td>Goodness of Fit Index (GFI)</td><td>Adjusted Goodness of Fit Index (AGFI)</td><td>Normalized Fit Index (NFI)</td></tr><tr><td>Résultat</td><td>0.08</td><td>0.82</td><td>0.89</td><td>0.75</td><td>0.83</td><td>0.77</td><td>0.91</td></tr><tr><td>Règle générale</td><td>≤ 0.06 ~ 0.08</td><td>≥0.90</td><td>≥0.95</td><td>≥0.90</td><td>≥0.90</td><td>Intervalle [0, 1]</td><td>≥0.90</td></tr></table> Secondly, as depicted in the table below, the model's fit indices indicate a low level of adequacy. Measures such as Incremental Fit Index (IFI) = 0.82, Non-Normed Fit Index (NNFI) = 0.75, Goodness of Fit Index (GFI) = 0.83, and Adjusted Goodness of Fit Index (AGFI) = 0.77 fall below the minimum threshold of 0.90. Thirdly, confronted with a structural model characterized by weak causality coefficients and fit indices, specialists recommend undertaking model modifications based on suggestions automatically provided by LISREL. ### c) Post-HOC Model This process of modifying the structural model involves establishing new relationships between endogenous and exogenous variables based on the indices provided by Lisrel. With its sophisticated technology, Lisrel provides new relationship pathways that improve both the average value of chi-square and the regression coefficient between variables (see table). In truth, the issue of model re-specification remains a controversial topic in the specialized literature, with some researchers supporting the idea while others criticize it. Proponents of the first group argue that the goal of structural equation modeling is generally to develop the most parsimonious model that accurately captures relationships between variables, making model modification a key and crucial step in the analysis (Raykov and Marcoulides, 1999). Opponents in the second group caution that the "model improvement" technique makes the obtained model very specific to the sample and not generalizable to the entire reality. They recommend using this technique only in cases where the initial model shows a very low level of fit, with regression coefficients below 0.3. Table 7: Reliability of the measurement model <table><tr><td colspan="3">Indicators</td></tr><tr><td colspan="3">Socio-emotional wealth</td></tr><tr><td>x Factor Loading</td><td>Composite Reliability</td><td>Average Variance Extracted</td></tr><tr><td>,854</td><td>0.85</td><td>0.84</td></tr><tr><td colspan="3">Organizational Change Capability</td></tr><tr><td>,742</td><td>0,75</td><td>0.82</td></tr></table> In our case, the adjustment indices are below 0.90, and five regression coefficients are below 0.3, indicating that endogenous variables (Familiness, Emotional Attachment, Relational Synergy, Firm Identification) explain less than $30\%$ of the variance in their indicators. This reflects the weak convergence of the model (Fornell and Larcker, 1981). Therefore, model modification is inevitable. The basis for this Post-Hoc modification lies in the residual values and adjustment indices. LISREL directly conducts this type of analysis and provides these indicators in a table at the end of the syntax file (see the table below the post-hoc model). Table 8: Presentation of adjustment indices- AD-hoc model <table><tr><td>Indice</td><td>(RAMSEA)</td><td>Incremental Fit Index (IFI)</td><td>Comparative Fit Index (CFI)</td><td>Non-Normed Fit Index (NNFI)</td><td>Goodness of Fit Index (GFI)</td><td>Adjusted Goodness of Fit Index (AGFI)</td><td>Normalized Fit Index (NFI)</td></tr><tr><td>Résultat</td><td>0.08</td><td>0.91</td><td>0.96</td><td>0.93</td><td>0.94</td><td>0.92</td><td>0.94</td></tr><tr><td>Règle générale</td><td>≤ 0.06 ~ 0.08</td><td>≥0.90</td><td>≥0.95</td><td>≥0.90</td><td>≥0.90</td><td>Intervalle [0, 1]</td><td>≥0.90</td></tr></table> After testing all the paths proposed by Lisrel, the obtained post hoc model consists of two endogenous variables (emotional attachment, relational synergy) and three exogenous variables (climate of trust, empowerment culture, change champion). It reflects five direct relationships among them ## IV. DISCUSSION The examination of results reveals that Moroccan family firms engage in transformative initiatives for reasons deeply intertwined with socio- emotional wealth. These firms exhibit a strategic orientation toward change, driven by a the status of the emotional fabric within their organizational and familial realms. For instance, the pursuit of increased socio-emotional wealth emerges as a foundational motivation. Family firms recognize the intrinsic value of fostering emotional attachment and relational synergies. In situations where the consequences of implementing change are perceived to fortify emotional connections among family members and nurture positive relationships within the organizational environment, acceptance of the change becomes more likely. Consequently, resistance is expected to diminish. Also, the preservation of socio-emotional wealth stands out as a key impetus for change. Family firms view their socio-emotional wealth as a vital asset contributing to their identity, legacy, and internal cohesion. Changes are not only seen as growth-oriented measures but also as mechanisms to sustain and safeguard emotional bonds, trust, and a sense of responsibility within the family and the organization. In contrast, the minimization of losses in socio-emotional wealth represents a cautious yet crucial motivation. Family firms, while acknowledging the importance of emotional ties and relational dynamics, exercise prudence in implementing changes. The aversion to disruptive changes that may jeopardize socio-emotional wealth underscores a commitment to conserving the firm's identity, trust, and familial relationships. Another conclusion drawn from this study is that change management activities within Moroccan family SMEs are inherently emotional. This implies that the emotional state of the company, manifested through the level of attachment of family members to the business, the type of relationship established among organizational actors, and the company's social capital, determines its ability to develop cognitive (rational) and material change management skills. The model illustrates that two facets of socio- emotional wealth (Emotional Attachment, Relational Synergy) influence three change management capabilities (Trust, culture of responsibility, change champion) with an average factor value of 0.50. The significance of emotional weight in organizational change management remains a well-established observation, as numerous previous studies have highlighted. A study published in the Harvard Business Review in 2020, titled "Saving a Family Business from Emotional Dysfunction," emphasizes the importance of emotions, considering them as direct determinants of the survival of family businesses. The study by Manfred F. and R. Kets de Vries reveals that only three out of 10 family businesses survive to the second generation, and only one out of 10 is passed on to the third generation. They attribute this low survival rate to the direct consequences of poorly managed emotions, such as unfair treatment of heirs, lack of trust, and personalized relationships between the founder and stakeholders, which could lead the family firm to decline. Furthermore, a study conducted by Poder Pedersen at the University of Copenhagen in 2001 argues that emotion management is a tool that can either facilitate or complicate the implementation of change. The expression of empathy toward employees' emotional reactions can alleviate tensions (conflicts, rumors), while the expression of anger generates resistance. Poder (2001) concludes that emotions serve as a mechanism to control the reactions of actors involved in change. Effective management of emotions provoked during the storm is essential to reduce resistance and inertia factors among organizational actors. Another revelation of our ad-hoc model is evident in the timing of emotions. The dominant paradigm assumes that emotions are triggered within family organizations as a response from collaborators to change. In other words, they occur ex-post following the emergence of a stimulus (change in our case). The challenge for managers is to protect the company from these responses, which could be negative, manifesting as resistance, frustration, and refusal, or positive, through behaviors of acceptance and collaboration. This reactive logic, assuming that emotions occur after a change and only become significant post-appearance, dominates most scientific publications. Richard Lazarus's Appraisal theory (2010) adopts this logic, considering emotions as momentary subjective experiences when individuals evaluate a situation or face an unknown event. Similarly, the Sustainable Family Business Theory (SFBT) confirms this logic, suggesting that family and business are intertwined subsystems that evolve simultaneously. When an event affects one subsystem, it triggers a reaction in the other. In contrast, our model argues the opposite, asserting that emotions in Moroccan family SMEs have ex-ante importance. They are not merely psychological reactions to change but determinants of the family business's ability to cope with it. Based on this perspective, our model challenges the prevailing theories. In the visual interpretation of the model, three arguments support this proposition. Firstly, the emotional attachment of family members to the company facilitates the selection of change champions with a factor value of 0.49 connecting these two variables. Secondly, a strong social capital facilitates the establishment of a climate of trust, with a figure of 0.69 reflecting its impact. Thirdly, an interconnection between emotional attachment and a culture of responsibility is confirmed with a value of 0.43. A variety of recent research aligns with our perspective on the ex-ante importance of emotions. The article published by Franz W. Kellermanns et al. in 2014, titled "The role and impact of emotions in family business strategy: New approaches and paradigms," suggests that emotions within family businesses are not mere reactions but essential determinants of the company's strategy. According to Franz (2014), decisions such as choosing a successor, human resources practices, and relationships with stakeholders are significantly influenced by socio-emotional wealth. For example, founders often choose a successor who ensures two crucial emotional dimensions: preserving the family dynasty and ensuring the long-term viability of the business. Furthermore, Kathleen Randerson and Miruna Radu-Lefebvre in 2020 confirm this idea by asserting that the emotional ambivalence of family members impacts the decision-making process of family organizations. For instance, emotions like anger and rivalry lead to individualistic and selfish decisions such as layoffs and relationship ruptures. In addition from the ad-hoc model highlights the variability of the impact. It posits that socio-emotional wealth does not always positively impact the firm's ability to undergo change; in some exceptional cases, the affective capital has an inverse effect. While the structural model (ad hoc) asserts that emotional attachment facilitates the selection of change champions and social capital encourages the establishment of a climate of trust, it also suggests that excessive attachment to the business activity, a strong social capital, and historical relations with stakeholders limit the firm's capacity to explore new business domains and initiate disruptive changes. In other words, it is unlikely that business owners deeply attached to their activities would initiate drastic changes such as a change in the industry sector or the sale of part of the shares. An illustrative example is the Onassis Greek family, one of the wealthiest in Europe. Aristotle Onassis, the founder of the maritime transport company, was emotionally attached to his sons. Following their unexpected deaths in a plane crash, the company declared bankruptcy because Onassis could not explore a new path alone and could not withstand the changes in the board members. Research by Larraza-Kintana (2010) and Cruz et al. (2014) asserts that the strong presence of socio-emotional wealth hinders the implementation of changes. They argue that due to the specific identity (social image) developed by family owners through the intersection of the two subsystems (family and business), they become personally connected to the company often bearing their family name. Consequently, they avoid any kind of change that might distort this image or identity. Additionally, José Moyano-Fuentes (2020) adds that family firms avoid high-risk organizational changes to preserve socio- emotional wealth. In other words, owner-managers prioritize noneconomic objectives such as preserving the image, social capital, and dynasty over change if it poses risks of SEW losses. Exploring new business domains and initiating disruptive changes is unlikely for owners and managers deeply attached to the business activity. This includes launching drastic changes such as a change in the sector or selling part of the shares. A notable example in this context is the Onassis Greek family, among the wealthiest in Europe. Aristotle Onassis, the founder of the maritime transport company, was emotionally attached to his sons. Consequently, following their unexpected deaths in a plane crash, the company declared bankruptcy because Onassis couldn't explore a new path alone and couldn't bear the change in the board members. Research by Larraza-Kintana (2010) and Cruz et al. (2014) asserts that the strong presence of socio-emotional wealth hinders the implementation of changes. They argue that due to the specific identity (social image) developed by family owners through the intersection of the two subsystems (family and business), they become personally connected to the company, often bearing their family name. Consequently, they avoid any kind of change that might distort this image or identity. Additionally, José Moyano-Fuentes (2020) adds that family firms avoid high-risk organizational changes to preserve socio-emotional wealth. In other words, owner-managers prioritize noneconomic objectives such as preserving the image, social capital, and dynasty over change if it poses risks of CSR losses. Finally, the scarcity of usage represents the last form of influence exerted by socio-emotional wealth on the capabilities of Moroccan family SMEs to change. It describes the fact that the affective endowments of the organization (emotional attachment, relational synergy) certainly reinforce the skills necessary for change (change champion, culture of trust, and sense of responsibility), but their effective use by owner-managers is occasional, if not rare. The conservatism theory stipulates that family businesses, by definition, are not too open to organizational transformations; they often lean towards preserving their status quo. This implies that these entities rarely initiate change projects, typically only when the realization of the change directly threatens the survival of the business. Consequently, change capabilities are seldom utilized. ## V. CONCLUSION In conclusion, family enterprises in Morocco operate within a culturally rich and emotionally charged environment, where familial and societal values intricately intertwine, shaping their operational fabric. The study has highlighted the significance of cultural attributes, including collectivism, high power distance, and diversity, in influencing the understanding of socio-emotional wealth (SEW) within Moroccan family businesses. The emphasis on collectivism implies a societal orientation towards group cohesion and interdependence, impacting the perception and management of SEW within family businesses. Additionally, the prevalent high power distance and cultural diversity contribute layers of complexity to the dynamics of socio-emotional wealth within the business domain. Furthermore, the study has uncovered additional layers of complexity within Moroccan family businesses. The inherent inclination of these enterprises to preserve the status quo, deeply rooted in established identities and family names, poses challenges and potential missed opportunities for growth. The concept of ambidexterity gains significance in understanding how these family firms balance the preservation of proven practices with the exploration of potential avenues for growth. The research has explored how socio-emotional wealth contributes to ambidexterity in the face of change, enabling family firms to maintain their traditional identity, values, and successful business models while navigating change peacefully. The study has shed light on the intricate interplay of emotions, emphasizing their collective experience woven into the operational fabric of family businesses. In examining the results, it becomes evident that Moroccan family firms engage in transformative initiatives motivated by socio-emotional wealth, where the preservation and enhancement of emotional bonds, trust, and a sense of responsibility play crucial roles. The research also emphasizes the emotional nature of change management activities within these family businesses, with emotions serving as determinants of their ability to develop change management capabilities. The ad-hoc model developed in this study challenges prevailing paradigms by asserting the ex-ante importance of emotions in family SMEs. It suggests that emotional attachment, relational synergy, and social capital are not mere reactions to change but essential determinants of the family business's ability to cope with and initiate change. The model illustrates the nuanced impact of socio-emotional wealth on change management capabilities and emphasizes the variability of this impact. Moreover, the study reveals the scarcity of usage as a form of influence exerted by socio-emotional wealth on the capabilities of Moroccan family SMEs to change. Despite reinforcing the skills necessary for change, these emotional endowments are often underutilized, aligning with the conservatism theory that family businesses are generally resistant to organizational transformations. In summary, the findings contribute to the evolving discourse on the strategic adaptability and resilience of family businesses in Morocco. The recognition of emotions as proactive determinants, rather than reactive responses, challenges conventional perspectives and underscores the need for a nuanced understanding of socio-emotional wealth's impact on change dynamics within the familial business context.

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