Participative leadership, cultural factors, and speaking-up behaviour: An examination of intra-organisational knowledge sharing

Toufighi, Seyed Pendar et al. Article Participative leadership, cultural factors, and speakingup behaviour: An examination of intra-organisational knowledge sharing Journal of Innovation & Knowledge (JIK) Provided in Cooperation with: Elsevier Suggested Citation: Toufighi, Seyed Pendar et al. (2024) : Participative leadership, cultural factors, and speaking-up behaviour: An examination of intra-organisational knowledge sharing, Journal of Innovation & Knowledge (JIK), ISSN 2444-569X, Elsevier, Amsterdam, Vol. 9, Iss. 3, pp. 1-13, https://doi.org/10.1016/j.jik.2024.100548 This Version is available at: https://hdl.handle.net/10419/327450 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ Participative leadership, cultural factors, and speaking-up behaviour: An examination of intra-organisational knowledge sharing Seyed Pendar Toufighi a, *, Iman Ghasemian Sahebi b , Kannan Govindan c , Min Zar Ni Lin a , Jan Vang a , Annalisa Brambini a a University of Southern Denmark, ITI Department, GSP Section, Denmark b Department of Operations Management, Faculty of Management, University of Tehran, Iran c University of Southern Denmark, ITI Department, EOM Section, Denmark ARTICLE INFO Article History: Received 7 June 2024 Accepted 14 August 2024 Available online 21 August 2024 ABSTRACT This study examines the influence of participative leadership and cultural factors on employees’speaking-up behaviour and knowledge-sharing in supplier development initiatives in the garment industry. Specifically, this study investigates the impact of leadership effectiveness, cultural dimensions, and individual characteristics using surveys and interviews. Our findings indicate that participative leadership positively correlates with employee speaking-up behaviour. However, the analysis of variance (ANOVA) results show that language proficiency and region significantly influence employees’willingness to speak up, although the differences in knowledge-sharing scores across cultural groups are statistically insignificant. Mediation analysis further reveals that perceived leadership effectiveness partially mediates the relationship between participatory leadership and knowledge-sharing intentions. The interview findings provide deeper insights into the roles of cultural intelligence, communication barriers, and social identity in shaping knowledge flow. These findings offer practical implications for organisations seeking to enhance supplier development initiatives. To foster an inclusive environment that empowers employee voice and encourages collaborative knowledge sharing, organisations can adopt participative leadership, accommodate cultural and linguistic diversity, and promote effective leadership perceptions. We anticipate that future research will explore the generalisability of these findings across industries and examine additional cultural dimensions that influence knowledgesharing dynamics. © 2024 The Author(s). Published by Elsevier España, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Keywords: Supplier development Speaking-up behaviour Knowledge sharing Intervention-based research Participative leadership Garment industry JEL classifications: M11 L6 L210 C12 Introduction Global buyers have long been implicated in supplier development programmes in the Global South; the garment industry is particularly infamous for its performance (Bag et al., 2023;Vang et al., 2023). Compared to other industries, the garment industry offers a unique and valuable setting for examining supplier development owing to its intricate global supply chains and complex buyer−supplier dynamics requiring careful coordination and management (Gereffiet al., 2005). Supplier development programmes in the garment industry often involve joint buyer-supplier initiatives to improve quality, productivity, and sustainability. For example, buyers may provide training and resources to help suppliers upgrade their manufacturing processes, implement lean methodologies, or adopt eco-friendly practices (Hasle & Vang, 2021a). Unlike other industries, the garment industry’s supply chain is highly fragmented; suppliers are often located in developing countries while buyers are in developed markets (Gereffiet al., 2005). This geographical and cultural distance exacerbates communication barriers and hinders effective knowledge transfer between supply chain partners (Anderson et al., 2023; Asamoah et al., 2023;Nurhayati et al., 2023). Moreover, the garment industry faces intense competition, fast-paced product cycles, and stringent quality and compliance requirements (Jia et al., 2023). Hence, conducting supplier development programmes in the garment industry is essential to ensure quality, ethics compliance, and sustainability standards (Hasle & Vang, 2021;Jia et al., 2023;Vang et al., 2023). Moreover, implementing effective supplier development initiatives, particularly joint development initiatives (Krause & Krause, 1997), will enhance supply chain performance and foster mutually beneficial buyer-supplier relationships (F€ alt-Ollikainen, 2018;Saghiri & Mirzabeiki, 2021). Abbreviations: LMX, Leader-Member Exchange; PLS, Participatory Leadership; SPB, Speaking-up Behaviour; KSS, Knowledge-sharing Scores; DCG, Different Culture Groups; PLE, Perception of Leadership Effectiveness; KSI, Knowledge-sharing Issues * Corresponding author. E-mail address: [email protected] (S.P. Toufighi). https://doi.org/10.1016/j.jik.2024.100548 2444-569X/© 2024 The Author(s). Published by Elsevier España, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Journal of Innovation & Knowledge 9 (2024) 100548 Journal of Innovation &Knowledge https://www.journals.elsevier.com/journal-of-innovation-and-knowledge The organisational behaviour literature has extensively examined speaking-up behaviour and the voluntary expression of ideas, concerns, or opinions in improving organisational performance (Bergeron & Thompson, 2020;Frazier, 2013;Tedone & Bruk-Lee, 2022). While its relevance and implications in the context of supplier development initiatives remain underexplored, facilitating successful buyer-supplier relationships requires open communication, knowledge sharing, and expression of concerns and suggestions (Giannakis, 2008;Modi & Mabert, 2007;Wiratmadja & Tahir, 2021). Speaking up highlights potential issues in buyer-supplier relationships, encourages collaborative problem-solving, and ensures continuous improvement efforts. Cultural factors and leadership dynamics significantly influence speaking up and knowledge sharing in supplier development contexts (Salimian et al., 2017,2021). Specifically, cross-cultural differences in communication norms, power distance, and individualism-collectivism orientations influence employees’ willingness to express opinions and share information (Kwon & Farndale, 2020). Furthermore, leadership styles and perceived psychological safety within organisations are crucial in encouraging or discouraging speaking up and knowledge sharing (Edmondson & Lei, 2014), thereby impacting supplier development activities. Previous studies (Benton Jr et al., 2020;Gu et al., 2021) have extensively investigated supplier development from operational (Sillanp€ a€ a et al., 2015;Singh & Kumar, 2020) and strategic (Sillanp€ a€ a et al., 2015) perspectives. However, the understanding of how soft factors influence organisational behaviours and employee dynamics is limited (Chi et al., 2024;Long, 2024). Furthermore, the role of speaking-up behaviour and its impact on knowledge sharing and collaborative buyer-supplier improvement efforts have received limited attention in the supplier development literature (Morrow et al., 2016;Tucker, 2012). This study addresses this critical gap in the literature by examining the leadership and cultural dynamics in supplier development in Myanmar’s garment industry through speaking-up behaviour and knowledge-sharing perspectives. Specifically, it examines the influence of participative leadership, cultural factors, and individual background on employees’speaking-up behaviour and knowledge sharing. Myanmar’s garment industry, serving as a central manufacturing hub, is crucial to global supply chains. However, it faces various challenges, including low productivity, inconsistent quality, long lead times, and limited adoption of sustainable practices (Govindan et al., 2021). These constraints have hindered the industry’s ability to attract large international buyers and grow through exports (Hasle & Vang, 2021b). This study integrates insights from the organisational behaviour literature on speaking-up behaviour and knowledge sharing with the supplier development literature. This comprehensive approach aims to identify the mechanisms that promote or obstruct open communication and knowledge sharing during supplier development initiatives. It explores speaking-up behaviour and its antecedents, including leadership styles, cultural norms, and perceived psychological safety. An understanding of these dynamics can help buyers and suppliers create an environment in which employees are encouraged to collaboratively share their concerns and expertise and identify improvement areas (Nagati & Rebolledo, 2013;Rashidi & Saen, 2018). Moreover, this study addresses gaps in various literature streams. It introduces a novel perspective, emphasising the importance of soft factors, particularly speaking-up behaviour and knowledge sharing dynamics. This study integrates organisational behaviour concepts to comprehensively understand the complex interactions between buyer−supplier relationships, communication patterns, and continuous improvement efforts. Furthermore, this study recognises the potential impact of individual characteristics such as cultural background, language proficiency, and demographic factors on speakingup behaviour and knowledge-sharing tendencies. These individuallevel factors contribute to a deeper understanding of the complex interplay between organisational, cultural, and personal factors that influence supplier development practices. By integrating insights from the organisational behaviour and cross-cultural management literature, this study provides a more holistic understanding of the complex dynamics that shape communication and collaboration among garment workers and their supervisors. The rest of this paper is organised as follows. Section 2 presents the existing literature and hypotheses development. Section 3 describes the research methodology. Sections 4 and 5 detail the findings and discussion, respectively. Section 6 presents the conclusions, limitations, and directions for future research. Literature review Organisations’pursuit of supplier development initiatives is critical for enhancing supply chain performance and capability (Krause et al., 2007;Krause & Krause, 1997). When effectively implemented, these initiatives can bolster supply chain competitiveness by reducing costs, improving delivery reliability, and enhancing product quality (Modi & Mabert, 2007). Research has focused on the operational and strategic aspects of supplier development; however, the understanding of the role of soft factors, such as organisational behaviour dynamics and cultural influences (Suurmond et al., 2020), is lacking. Supplier development involves the long-term cooperative effort between a firm and its suppliers to improve supplier quality and performance (Krause & Krause, 1997). Suppliers are evaluated as part of conventional supplier development strategies; their performance is measured and direct assistance on quality management, process improvement, and product development is provided (Krause & Ellram, 1997b,1997a). However, the human and behavioural factors that significantly impact the effectiveness of supplier development initiatives are often overlooked. The importance of knowledge sharing for organisational success has been well-documented in the literature. Recent studies have explored the role of leadership styles in encouraging knowledgesharing behaviours among employees. For instance, Khatoon et al. (2024) found that empowering leadership, directly and indirectly, enhances employees’knowledge sharing through psychological empowerment; this relationship is further strengthened by employees’learning goal orientation (Khatoon et al., 2024). Chaudhary et al. (2023) examined the influence of paternalistic leadership, along with its benevolent, moral, and authoritarian dimensions, on nurses’ knowledge sharing, revealing that affective and normative organisational commitment mediate this relationship. Furthermore, work ethics moderate the link between organisational commitment and knowledge sharing (Chaudhary et al., 2023). Islam et al. (2024) explored how knowledge sharing facilitates innovative work behaviour; occupational self-efficacy mediates this relationship, while entrepreneurial leadership strengthens it (Islam et al., 2024). Islam and Asad (2024) found that entrepreneurial leadership enhances employee creativity. This relationship is explained by knowledge sharing, with creative self-efficacy moderating the association between knowledge-sharing and creativity association (Islam & Asad, 2024). Collectively, these studies highlight the complex interplay between leadership styles, organisational factors, individual characteristics, and knowledge-sharing dynamics, providing a valuable foundation for this study. Knowledge sharing enhances organisational learning and continuous improvement (Argote et al., 2000;Argote & Ingram, 2000). Buyer−supplier knowledge sharing is vital for supplier development because it can facilitate the transfer of best practices, identify improvement areas, and promote collaborative problem resolution (Modi & Mabert, 2007). Several factors can hinder knowledge sharing in inter-organisational contexts, including lack of trust, divergent organisational cultures, and lack of effective communication (EasterbySmith et al., 2008). A deeper understanding of the facilitators and S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 2 enablers of knowledge sharing, including leadership support, shared goals, and cultural compatibility, is required to overcome these obstacles (Khalfan et al., 2007). Leadership effectiveness influences organisational outcomes and employee behaviour (Yukl, 2012). A company’s leaders’perceptions of trustworthiness, willingness to receive feedback, and empowerment can affect employees’motivation and confidence in speaking up and sharing knowledge (Detert & Burris, 2007;Srivastava et al., 2006). The influence of cultural factors on communication patterns, knowledge-sharing norms, and supplier development initiatives cannot be overstated (Lakemond et al., 2006). Cultural dimensions, such as power distance and individualism-collectivism, can influence employees’willingness to voice their opinions and share information (Hofstede, 2011). The quality and extent of information exchange between buyers and suppliers may also be affected by individual characteristics such as region and language proficiency (Simpson & Power, 2005). Speaking-up behaviour—the voluntary expression of ideas, concerns, or opinions to improve organisational performance—is a crucial aspect of organisational dynamics (Detert & Edmondson, 2011). This process encourages employees to voice their suggestions, concerns, or dissenting views on organisational practices or policies (Li et al., 2020). Several factors, including leadership style, organisational culture, and perceived psychological safety, influence speaking-up behaviour (Edmondson & Lei, 2014). For instance, participatory leadership encourages employees to contribute their input and opinions, fostering a culture of psychological safety and trust and increasing employees’willingness to speak up (Detert & Burris, 2007). Furthermore, organisations that value employee contributions and promote open communication are more likely to encourage employee speaking-up behaviour (Milliken et al., 2003), leading to a more engaged and empowered workforce. Hypotheses development In this study, we examine the applicability of speaking-up behaviour and its antecedents in the unique context of supplier development to contribute to the literature on organisational behaviour. We explore how participatory leadership (H1) and employee perceptions of leadership effectiveness (H3) particularly influence speaking up and knowledge-sharing tendencies within a cross-organisational setting. It sheds light on the role of speaking-up behaviour in interorganisational collaboration by expanding speaking-up behaviour beyond the traditional intra-organisational context. We acknowledge that cultural factors significantly impact employee behaviour and organisational dynamics. Investigating the effect of cultural norms, such as speaking up and backgrounds (H2), and individual characteristics like region and language proficiency (H4), contributes to the cross-cultural management literature. It enhances the understanding of how cultural influences shape communication patterns, knowledge-sharing practices, and the effectiveness of supplier development initiatives in diverse cultural contexts. Furthermore, this study contributes to knowledge management and organisational learning by examining how speaking-up behaviour and knowledge sharing can facilitate continuous improvement and collaborative buyer−supplier learning. To promote mutual learning and improvement opportunities, this study explores the mechanisms through which cultural factors, leadership dynamics, and individual characteristics influence knowledge exchange and integration across organisational boundaries. We propose a novel theoretical framework, drawing from the supplier development, organisational behaviour, and cross-cultural management literature. This framework offers a unique perspective on the interaction between leadership styles, cultural differences, and individual characteristics in shaping knowledge sharing and speaking-up behaviour within the context of supplier development initiatives. Participatory leadership, which champions employee involvement in decision-making processes and values employees’contributions, enhances employee commitment, motivation, and job satisfaction. This approach, rooted in the literature, posits that employees thrive when involved in decisions that impact their work (Magbity et al., 2020;Somech, 2005). This offers hope for organisations seeking to foster a culture of open communication and knowledge sharing. Leader-Member Exchange (LMX) theory suggests that leaders are responsible for establishing unique relationships with their followers; the quality of these relationships influence various workplace outcomes, including employee voice behaviour (Hasib et al., 2020;Omilion-Hodges et al., 2021). Leadership that encourages participation will likely foster high-quality LMX relationships characterised by trust, respect, and open communication, motivating employees to speak out without fear of negative consequences (Cheung & Wu, 2014). Speaking-up behaviour is more likely to occur when employees feel psychologically safe. In a psychologically safe workplace, participatory leaders value employee input, encourage open communication, and employ a non-punitive approach to mistakes and dissenting opinions (Detert & Edmondson, 2011). Additionally, social interactions are often motivated by the expectation that others will treat them favourably or that their actions will be reciprocated (Cropanzano & Mitchell, 2005). Several empirical studies have found that participatory leadership and employee speaking up are positively related (Bao et al., 2021;Sax & Torp, 2015;Tedone & Bruk-Lee, 2022). Detert and Burris (2007) demonstrated that open communication and employee involvement in decision-making are essential for fostering a psychologically safe workplace. Tangirala and Ramanujam (2008) discovered that employees are more likely to speak up if they perceive their leaders as open to their input and include employees in their decision-making processes. Managing employees using a participatory approach and rewarding their contributions creates a sense of obligation and reciprocity, increasing employees’willingness to share their thoughts and concerns (Detert & Burris, 2007). Moreover, participatory leadership can catalyse open communication and buyer−supplier knowledge sharing in the garment industry. It is instrumental in fostering collective problem solving in day-to-day operations by leveraging workers’ideas and insights to improve operations. Open communication and knowledge sharing can lead buyers and suppliers to engage in collaborative problem solving, continuous improvement, and effective transfer of best practices across the supply chain, instilling confidence in the proposed framework. Based on this discussion, we propose the following hypothesis. H1: Participatory leadership positively influences employee speaking-up behaviour within garment factories. Hofstede’s cultural dimensions theory posits that cultural values and norms influence an individual’s attitudes, behaviours, and communication. Knowledge-sharing behaviours within organisations are influenced by power distance, individualism-collectivism, and uncertainty avoidance (Suppiah & Singh Sandhu, 2011). For example, in high power distance cultures, employees may feel intimidated about challenging those in higher positions, thereby reducing their willingness to share knowledge (Michailova & Hutchings, 2006). Ardichvili et al. (2006) reported low knowledge sharing in virtual teams due to the cultural values of individualism and distance. Research has demonstrated that cultural factors influence knowledge sharing (Abili et al., 2011;Azeem et al., 2021;Setini et al., 2020;Vajjhala & Baghurst, 2014). For instance, knowledge sharing may be hindered in cultures emphasising individual achievement and competition (Ardichvili et al., 2006). Employees’cultural backgrounds significantly influence supplier development. These cultural factors shape their perceived social identity and willingness to share knowledge with ‘outsiders’ S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 3 or members of different cultural groups (Choi et al., 2023;Ipe, 2003; Usanova et al., 2023). This underscores the importance of understanding and addressing cultural differences in fostering effective knowledge sharing in supplier development initiatives. A critical component of the knowledge governance approach involves recognising that several formal and informal factors such as organisational culture, norms, and values, including communication styles, trust levels, and shared values, influence knowledge sharing within and across organisations (Pemsel et al., 2016;Van Kerkhoff & Pilbeam, 2017). Specifically, these factors, which are informal governance mechanisms or unwritten rules guiding behaviour, support or impede knowledge sharing (Suppiah & Singh Sandhu, 2011). Employee behaviour and decisions are influenced by an organisation’s shared values, beliefs, and norms (Bagga et al., 2023). A team culture encompassing shared values, norms, and practices, including openness, collaboration, and trust, facilitate knowledge sharing. Conversely, a team culture involving secrecy, competition, and suspicion inhibits it (D. W. De Long & Fahey, 2000). Cultural factors significantly affect buyer−supplier knowledge sharing in the garment industry (Tran et al., 2023;Zare et al., 2023). Cultural differences in communication, trust levels, and values may hinder effective knowledge exchange and collaborative problem solving (Aslam et al., 2023;Zheng et al., 2024).)To facilitate supplier development initiatives, organisations must consider these cultural factors and develop strategies to bridge cultural gaps, foster shared understanding, and cultivate an environment conducive to open communication and knowledge sharing. Based on this discussion, we propose the following hypothesis. H2: Cultural factors significantly impact employee knowledge sharing within garment factories. The central hypothesis of this study proposes that perceived leadership effectiveness mediates the relationship between participative leadership and employee knowledge-sharing behaviour. This is because influential leaders’behaviours and actions positively influence various outcomes, including employee attitudes, motivation, and performance, in achieving organisational objectives. Specifically, employees are more likely to engage in positive behaviours such as knowledge sharing when they perceive their leaders as effective, trustworthy, and competent (Cropanzano & Mitchell, 2005;Srivastava et al., 2006), trusting that their contributions will be valued and appropriately utilised. This highlights the significant role that employee perceptions play in the knowledge-sharing process, empowering employees to contribute to the organisation’s growth and success. Previous research has demonstrated that perceived leadership effectiveness significantly mediates the relationship between leadership styles and knowledge-sharing behaviours (Connelly & Kevin Kelloway, 2003;Lin et al., 2020). Effective leaders foster an environment conducive to knowledge exchange by promoting trust, support, and open communication. Therefore, participative leadership practices alone may not directly lead to increased knowledge sharing. Instead, employees’perceptions of whether their participative leaders are practical and capable of creating a psychologically safe environment are critical intervening mechanisms facilitating knowledge sharing during supplier development initiatives. Based on this discussion, we propose the following hypothesis. H3: Perceived leadership effectiveness mediates the relationship between participatory leadership and employee knowledge sharing. Individuals adapt and function effectively in various situations because of their cultural intelligence and preferences (Thomas et al., 2015). Cultural intelligence comprises four dimensions: cognitive, metacognitive, motivational, and behavioural (Earley & Ang, 2003). A critical factor in individual adaptability in a cross-cultural context, cultural intelligence can significantly influence effective communication and knowledge sharing. Employees with high cultural intelligence tend to demonstrate effective communication and knowledgesharing skills and better navigate cultural differences. In cross-cultural contexts, group identities may influence an individual’s attitude, behaviour, communication style, and willingness to share information. Our hypothesis focuses on group-level variations based on regional or linguistic backgrounds, aligning more with functional heterogeneity rather than individual cultural intelligence. Functional heterogeneity posits that team or organisational diversity can enrich or hinder knowledge sharing and collaboration. In Myanmar’s garment industry, employees’speaking-up behaviour and knowledge-sharing tendencies may vary according to their backgrounds such as region or language. Individuals’comfort levels in expressing ideas, concerns, or expertise may vary depending on cultural norms, linguistic barriers, and regional differences, particularly in cross-cultural buyer−supplier interactions. Understanding these individualised factors helps organisations develop strategies for facilitating effective communication and knowledge sharing across diverse employee groups. Therefore, it may be necessary to provide language training, foster cultural intelligence, and establish inclusive environments that value diversity and promote knowledge sharing and collaboration while addressing potential barriers to collaboration. Based on this discussion, we propose the following hypothesis. H4: Employees from diverse backgrounds, such as different regions or language groups, exhibit variations in their speaking-up behaviour and knowledge-sharing tendencies. Material and methods To address the research questions, we conducted a case study on Myanmar’s garment industry using intervention-based research. Myanmar’s garment industry, characterised by diverse cultural backgrounds and buyer−supplier relationships, provides a rich foundation for our study. We utilised a mixed methods approach as it suits our research goals, allowing the integration of numerical data and indepth insights to elucidate the phenomena under investigation. Quantitative surveys enabled the assessing of statistical relationships between the key variables—participative leadership, cultural groups, and communication/knowledge-sharing behaviours. Qualitative interviews were conducted to complement the quantitative data, offering deeper insights into the underlying mechanisms, contextual factors, and individual experiences influencing these dynamics. Using a mixed methods approach enabled us to gain a holistic and contextualised understanding of how soft factors, including leadership styles and cultural influences, affect supplier development initiatives and collaborative improvement efforts between buyers and suppliers. This comprehensive mixed methods design aligns with the study’s aim of uncovering the complex interplay between organisational, cultural, and individual-level factors influencing open communication and knowledge exchange within Myanmar’s garment industry. We developed and pre-tested a structured questionnaire to collect data from employees involved in supplier development initiatives in Myanmar’s garment industry. The questionnaire comprised reliable and validated scales measuring different variables, guaranteeing data accuracy. These variables include participatory leadership, speakingup behaviour, knowledge sharing, perceived leadership effectiveness, cultural dimensions (such as power distance and individualism-collectivism), and demographic variables. The questionnaire was translated into relevant languages to ensure accurate responses and comprehension. S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 4 In the qualitative phase of the study, we conducted in-depth, semi-structured interviews with several employees and leaders involved in supplier development initiatives. The interviews explored the nuances of leadership dynamics, cultural influences, influence of peers and leadership communication, engagement mechanisms, and individual experiences related to speaking-up behaviour and knowledge sharing. The interview questionnaire was based on initial observations made during the intervention in factories and the literature review. Before the actual interviews, we conducted a pilot test with five frontline workers to test their reflections in terms of language, concepts, and so on. The interview questionnaire was slightly updated thrice once responses to a particular question became saturated or further exploration was required. Frontline workers (sewing operators and helpers) and line supervisors/leaders from the sewing production line were interviewed, following a purposive sampling method (based on gender, rural/urban, migrant and non-migrant, and Burmese or non-Burmese ethnicity). All respondents were involved in supplier development activities. We aimed to observe/ understand respondents’experiences through their involvement in supplier development interventions. To minimise time constraints and reduce potential social desirability bias in the responses regarding supervisors or the factory, interviews were conducted over the phone, in Burmese, outside the factory on Saturday afternoons or Sundays. Interviews with line supervisors/leaders were conducted over a digital platform (Zoom or Viber). Additionally, to minimise gender and age disparities, interviews were conducted by two female research assistants whose ages were within the range of many respondents. Typically, each interview lasted between 45 and 90 min. In the quantitative phase of the study, a purposive sampling technique was used to ensure adequate representation of employees from different cultural backgrounds, regions, and language groups. The survey was administered in person considering the target population’s accessibility and preferences. Nugraha et al. (2022) documented that a professional data gathering service provides reliable access to high-quality data. Thus, a team of local consultants, trained by the researchers involved, distributed the pretested questionnaire; a total of 459 individuals were surveyed. The system distributed 520 questionnaires, of which 472 were returned; 13 were rejected as they lacked data. According to Krejcie and Morgan (1970), the required sample size for a population of 6585 production workers from 9 selected factories is 459; the returned responses exceeded the required sample size. Each response was assessed using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Table 1 displays the factors, subfactors, items, and sources. We used regression analysis to test Hypothesis 1, while Analysis of Variance (ANOVA) was employed to test Hypotheses 2 and 4. Mediation analysis was conducted to test Hypothesis 3, examining whether perceived leadership effectiveness mediates the relationship between participatory leadership and knowledge sharing. The composition of the external teams (e.g. buyers and suppliers) involved in the supplier development initiatives was kept constant across all cases to isolate regional and linguistic diversity effects within the local teams. The external teams comprised individuals from the same cultural and linguistic background, thereby controlling for any potential variations introduced by diversity. This approach allowed us to examine regional and linguistic heterogeneity influences, specifically within the local teams, without confounding the effects of cultural differences from the external teams. The survey design, which enabled the data collection team to follow up with the targeted respondents, primarily affected the survey’s unbiased response rate. The quantitative data was triangulated with qualitative interviews (follow-up interviews, supplementary focus group interviews, and workshops) with 53 frontline workers (Nielsen et al., 2020). Table 2 presents the respondents’demographic characteristics. Most respondents (40 %) had less than one year of work Table 1 Constructs related to the questions. Abbreviation Variable Question PLS Participatory Leadership Is ‘Arr Nar Del’the appropriate way to approach a supervisor or senior management member to raise process issues or challenges in the presence of others? Do leaders/supervisors not prefer discussing their process weak points or challenges in the presence of others? Could negative consequences (such as pressure, revenge, and so on) be caused by sharing process challenges or raising concerns that could cause the immediate supervisor to lose face? Does your supervisor/leader know what the best options are? SPB Speaking-up Behaviour Do you sympathise with the line leader/supervisor’s challenges due to pressure from higher supervisors/senior management? Is it appropriate to suggest or share thoughts without having solid information or a concrete solution? Is it appropriate to raise issues directly with a higher supervisor/senior management member without consulting the immediate leader/supervisor? Can employees share discussions with outsiders or local authorities (such as the police)? Is it appropriate to suggest or share thoughts ahead of other colleagues without consulting the group? Are you hesitant about sharing your thoughts in the presence of others, or do you dislike losing face among colleagues if you cannot answer counter questions posed by supervisors/senior management? Is it necessary to raise issues or suggest process challenges to the supervisor/senior management if you have plans to move to another factory? Is it appropriate to share thoughts or discuss seniority (ageand position-based) with others? Does providing suggestions or engaging in discussions waste your time and affect your daily production target? KSS Knowledge-sharing Scores To what extent do you share sewing-related knowledge (or) do you seek in your production line? Or your factory? DCG Different Culture Groups What is your native place group? PLE Perceived Leadership Effectiveness What is your view on your line leader’s leadership style and relationship with you, particularly regarding their openness to listening to new ideas and suggestions? What is your view on your line leader’s leadership style and relationship with you, particularly regarding their availability for consultation on difficulties/problems? What is your view on your line leader’s leadership style and relationship with you, particularly regarding their accessibility for discussing emerging problems (easily approachable)? KSI Knowledge-sharing Issues To what extent have you refrained from sharing your thoughts, even though you had something to share/discuss with your leader/supervisors of the factory? To what extent do you share sewing-related knowledge (or) do you seek in your production line? Or your factory? In the last month, have you talked/discussed with someone from other production lines (or) another department in this factory regarding production-related issues (production target, defects, sewing techniques)? LGP Proficient Language Do you mainly use the Burmese language to communicate with colleagues and family? S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 5 experience. Female operator responses (95 %) exceeded male responses. Results Table 3 presents the means, standard deviations, and correlations among the study variables. Table 3 and Fig. 1 reveal strong positive correlations between participatory leadership style (PLS) and speaking-up behaviour (SPB) (0.77), perceived leadership effectiveness (PLE) (0.76), and knowledge-sharing intention (KSI) (0.57). Similarly, knowledge-sharing score shows strong positive correlations with KSI (0.86) and moderate to strong positive correlations with SPB (0.62), PLE (0.59), and language proficiency (LGP) (0.69). Conversely, demographic/cultural group (DCG) exhibits very low correlations with other variables, suggesting that it may not significantly impact the other variables. This heatmap effectively highlights the key relationships, emphasising the strong associations between participatory leadership and knowledge-sharing-related behaviours and perceptions. The high correlation of 0.9 between PLE and SPB indicates potential multicollinearity concerns. To address this, we conducted additional diagnostic tests, including variance inflation factor (VIF), on the variables in the regression models. The VIF values were below the recommended threshold of five, suggesting that multicollinearity was not a significant issue in the analysis. The standard deviations of some variables such as DCG (4.298) and PLS (1.327) are relatively high compared to the mean values. This suggests a considerable spread in the data, which could be due to the sample’s diverse cultural and demographic characteristics. Table 2 Sample profile and respondents’demographic information. n% n% Gender Age group Male 25 5 <20 41 9 Female 434 95 20−24 165 36 Education 25−29 134 29 Primary school and below 51 11 30−34 65 14 Middle school 228 50 ≥35 54 12 High school 151 33 Duration at current factory Tertiary (including university students) 28 6 <1 year 183 40 Position 1−2 years 64 14 Sewing operator 376 83 2−3 years 76 17 Helper/Ironer 71 15 >3 years 136 30 Other 10 2 Table 3 Descriptive statistics and correlations between study variables. Variable Mean SD 1. PLS 3.08 1.327 2. KSS 2.62 1.072 3. DCG 4.94 4.298 4. SPB 3.04 0.897 5. PLE 3.14 0.883 6. KSI 2.64 0.903 7. LGP 2,63 0.974 Fig. 1. Correlation heatmap of study variables. S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 6 H1 was tested using linear regression analysis. The independent and dependent variables were PLS and SPB, respectively. The analysis also included control variables for employee demographics and organisational characteristics, although these variables are not specified in the output. The model summary (Table 4) provides an overview of the regression model’sfit. The R-squared value of 0.596 indicates that 59.6 % of the variance in SPB is explained by the independent variable PLS; control variables are included in the model. However, other factors not included in the model may also contribute to the remaining variance. The ANOVA results (Table 5) assessed the overall significance of the regression model. The F-statistic of 672.808 with a p-value of 0.000 (less than the conventional significance level of 0.05) suggests that the regression model is statistically significant. This indicates that the independent (PLS) and control variables collectively and significantly influence the dependent variable (SPB). Table 6 provides information on the individual predictors in the regression model. The unstandardised coefficient (B) for PLS is 0.521, with a standard error of 0.020. A standardised coefficient (beta) of 0.772 indicates that a one-unit increase in PLS is associated with a 0.772 standard deviation increase in SPB, holding all other variables constant. The t-statistic of 25.939 with a p-value of 0.000 (less than 0.05) for PLS suggests that the independent variable (PLS) has a statistically significant influence on the dependent variable (SPB), after controlling for other variables in the model. As shown in Fig. 2, the regression analysis results support H1, indicating that PLS significantly influences SPB among employees. The positive and statistically significant coefficient for PLS suggests that higher PLS levels are associated with increased SPB among employees. When interpreting these results, the study’s context, measurement scales used, and any potential limitations or assumptions underlying the regression analysis should be considered. In summary, after controlling for employee demographics and organisational characteristics, the regression analysis supports the hypothesis that PLS positively influences SPB among employees in supplier development interventions.H2 was tested using ANOVA. ANOVA was used to compare the mean knowledge-sharing scores (KSS) across DCG. The ANOVA results presented in Table 7 show an F-statistic of 1.162 and a p-value of 0.320. As the p-value is more significant than the conventional significance level of 0.05, no statistically significant difference exists in the mean KSS scores among DCG. The lack of statistically significant differences does not necessarily imply that cultural factors do not affect knowledge sharing. There could be other cultural dimensions or aspects not captured by the grouping variables used in the analysis. Additionally, the sample size within each cultural group may have been insufficient to detect significant differences. Interpreting these results should also consider the study’s context, measurement scales used for knowledge sharing, and any potential limitations or assumptions underlying the ANOVA. In summary, the one-way ANOVA does not support the hypothesis that cultural factors significantly impact knowledge sharing among employees during supplier development interventions. However, further research and analysis are required to fully understand the Table 4 Overview of the regression model’sfit. Model R R-squared Adjusted R-squared Std. Error of the Estimate 1 0.772 a 0.596 0.595 0.571 a. Predictors: (Constant), PLS, b. Dependent Variable: SPB. Table 5 ANOVA results for H1. Model Sum of Squares df Mean Square F Sig. 1 Regression 219.389 1 219.389 672.808 0.000 b Residual 149.018 457 0.326 Total 368.407 458 a. Dependent Variable: SPB, b. Predictors: (Constant), PLS. Table 6 Individual predictors in the regression model. Model B Std. Error Std. Coefficients, Beta t Sig. 1 Constant 1.429 0.067 21.179 0.000 PLS 0.521 0.020 0.772 25.939 0.000 a. Dependent Variable: SPB. Fig. 2. Significant relationship between PLS and SPB. S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 7 relationship between cultural factors and knowledge sharing in this context. H3 was tested using mediation analysis, which estimated the mediating effect of PLE on the relationship between PLS and KSI. For this purpose, we used SPSS regression analysis and Sobel test. Details can be found in Baron and Kenny (1986),Sobel (1982),Goodman (1960), and MacKinnon et al. (1995). The results of the two-stage regression analysis between PLS and PLE, and PLE and KSI are summarised in Table 8. Using the B coefficients and standard errors in the online Sobel test, the critical ratio was calculated to test whether the indirect effect of PLS on KSI via the mediator is significantly different from zero. Table 9 presents the results of Sobel test. The most important parameter here is the p-value, which is less than 0.05. Therefore, we can conclude that the indirect effect between PLS and KSI through PLE is statistically significant (p-value ≤0.05). To obtain the point estimate of the indirect effect at which the p-value in the Sobel test is statistically significant, we calculated the unstandardised beta coefficient: ð0:502 0:715Þ¼0:359. H4 was tested using ANOVA test of independence. Tables 10−13 show the ANOVA test of independence between the background characteristics, speaking-up behaviour, and knowledge-sharing tendencies. As the p-values of SPB among DCG and KSI among DCG are greater than the conventional significance level of 0.05, no statistically significant association exists between region and SPB and KSI. The p-values in the tables show statistically significant associations between language proficiency and SPB and KSI. Fig. 3 highlights the significant and non-significant associations between background characteristics and the dependent variables. The F-statistic values for each test are displayed; the dashed red line represents the conventional significance threshold (F= 5). Fig. 3 shows that the F-statistics for SPB among DCG and KSI among DCG are below the threshold, indicating no statistically significant differences in SPB and KSI across different cultural groups. In contrast, the F-statistics for SPB among LGP and KSI among LGP exceed the Table 7 ANOVA results −KSS among DCG. Sum of Squares df Mean Square F Sig. Between Groups 10.680 8 1.335 1.162 0.320 Within Groups 515.687 449 1.149 Total 526.367 457 Table 8 Path coefficients and std. errors. Path B Coefficient Standard Error A: PLS - PLE 0.502 0.020 B: PLE - KSI 0.715 0.034 Table 9 Sobel test results. Test Statics Standard Errors p-value 16.56741928 0.0227103 0.000 Fig. 3. ANOVA test of independence results. Table 10 ANOVA results −SPB among DCG. Sum of Squares df Mean Square F Sig. Between groups 306.018 31 9872 0.517 0.986 Within groups 8137.146 426 19.101 Total 8443.164 457 Table 11 ANOVA results −SPB among LGP. Sum of Squares df Mean Square F Sig. Between groups 194.528 31 6.275 6.566 0.000 Within groups 408.099 427 0.956 Total 602.627 458 Table 12 ANOVA results −KSI among DCG. Sum of Squares df Mean Square F Sig. Between groups 278.126 12 23.177 1.263 0.238 Within groups 8165.038 445 18.348 Total 8442.164 457 Table 13 ANOVA results −KSI among LGP. Sum of Squares df Mean Square F Sig. Between groups 236.577 12 19.715 24.021 0.000 Within groups 366.050 446 0.821 Total 458 S.P. Toufighi, I. Ghasemian Sahebi, K. Govindan et al. Journal of Innovation & Knowledge 9 (2024) 100548 8