Does green knowledge management build successful green ventures in the presence of innovative practices and knowledge-sharing behaviour

He, Mingqiang; Chang, Tin-Chang; Chenggang, Wu; Kien, Pham Van Article Does green knowledge management build successful green ventures in the presence of innovative practices and knowledge-sharing behaviour Journal of Innovation & Knowledge (JIK) Provided in Cooperation with: Elsevier Suggested Citation: He, Mingqiang; Chang, Tin-Chang; Chenggang, Wu; Kien, Pham Van (2024) : Does green knowledge management build successful green ventures in the presence of innovative practices and knowledge-sharing behaviour, Journal of Innovation & Knowledge (JIK), ISSN 2444-569X, Elsevier, Amsterdam, Vol. 9, Iss. 4, pp. 1-11, https://doi.org/10.1016/j.jik.2024.100618 This Version is available at: https://hdl.handle.net/10419/327520 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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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/ Does green knowledge management build successful green ventures in the presence of innovative practices and knowledge-sharing behaviour Mingqiang He a , Tin-Chang Chang b , Wu Chenggang c , Van Kien Pham d,* a Zhejiang Shuren University, China b Department of Marketing and Logistics Management, National Penghu University of Science and Technology, Taiwan c Zhuhai City Polytechnic College of Marxism, Guangdong Province, China d Department of Science, Technology and International Projects, Ho Chi Minh City University of Economics and Finance (UEF), Vietnam ARTICLE INFO JEL Code: D80 M15 O32 Keywords: Knowledge sharing Green knowledge creation Innovative practices Knowledge application Knowledge storage Knowledge Acquisition Successful Green Ventures Vietnam ABSTRACT The cumulative stress to acknowledge environmental challenges bound businesses to embrace sustainable practices into their business operations. In Vietnamese context, green ventures are considered a key contributor, hence, play major part in transformative landscape. Therefore, the study finds an opportunity to explore the effectiveness of green knowledge management practices on the success of Vietnam’s green ventures particularly in the presence of innovative practices and knowledge sharing behavior. Drawing upon Knowledge-Based Dynamic Capabilities View, the study extends the literature by exploring knowledge management through four dimensions namely are green knowledge creation, knowledge acquisition, knowledge application and knowledge storage in order to assess their collective impact on green ventures. The background of the research is embedded in the cruciality to build understanding that how Vietnamese manufacturing firms can have leverage on green knowledge management practices to achieve long-term sustainability. Results gauged through PLS-SEM model reveal that knowledge storage has a positive and significant impact on successful green ventures. Findings also reveal that innovative practices significantly mediate the relationship of knowledge creation and knowledge storage with successful green ventures. In addition to this, knowledge sharing behavior also mediates the association of knowledge application, knowledge storage and knowledge creation with successful green ventures. The study adds comprehensive knowledge explaining that knowledge sharing culture amplifies the benefits crafted from knowledge management practices, making organizations more innovative and resilient. Despite insightful findings, the study has limitation in terms of small sample size, hence, future studies are recommended to expand the sample size to generalize the findings in a broader context. Introduction The Industrial Revolution created employment and income for millions of people and initiated the global phenomenon of economic growth. However, it has also put a great strain on the natural environment by increasing over-consumption of natural resources, which has led to ecological deterioration and climate change across the globe (Arslan et al., 2022; Subramanian, 2018). Knowledge management (KM) has garnered significant scholarly attention owing to its potential to promote sustainable development in an organization (Chopra et al., 2021; Hussain et al., 2022). KM is widely recognized as a valuable strategic asset for organizations of all sizes and categories, in streamlining the creation, communication, sharing and effective implementation of collective knowledge within a company. KM is a particular determinant of sustainable development for firms focused on sustainable business practices. This interplay of KM and sustainable development has prompted a fundamental shift in the organization’s perception of how KM boosts the progress of an organization in a sustainable fashion. Therefore, there is a surge in the organizational focus on the integration of KM into the routine practices and processes within the organization. As a result, KM has arisen as a fresh approach that connects the existing condition with the organization’s sustainability aspirations and targets, helping to bridge the gap between the two (Chang et al., 2018; Yousaf et al., 2021). The existing literature * Corresponding author. E-mail addresses: [email protected] (M. He), [email protected] (T.-C. Chang), [email protected] (W. Chenggang), [email protected] (V.K. Pham). Contents lists available at ScienceDirect Journal of Innovation & Knowledge journal homepage: www.elsevier.com/locate/jik https://doi.org/10.1016/j.jik.2024.100618 Received 30 October 2023; Accepted 27 October 2024 Journal of Innovation & Knowledge 9 (2024) 100618 Available online 16 November 2024 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/ ). emphasizes the exploration of the impact of KM on the advancement of sustainability in various domains (Abbas & Sa˘ gsan, 2019; de Guimar˜ aes et al., 2018; Martins et al., 2019; Ribeiro et al., 2018; Shahzad et al., 2020). Nonetheless, Green Knowledge Management remains a novel concept, therefore, there is a significant scarcity of research in the area of green KM and its role in sustainable development and green ventures of organizations (Streimikiene & Akberdina, 2021; Wang et al., 2022). In addition, knowledge acquisition has been recognized as a primary factor in the learning cycle as it supports the continuous development and expansion of the knowledge repository of an organization. Therefore, scholars have been highlighting how the knowledge acquisition encourages the innovative practices of firms (Dat et al., 2022; Hirose Nishihara, 2018). Since the global manufacturing landscape experiences rapid evolution, therefore, incorporation of sustainability is now viewed as hypercritical dilemma in academia especially in the case of emerging economies. Particularly talking about Vietnam, the manufacturing industry of the country struggles hard to maintain its environmental performance while embracing sustainable practices into their operations. Although, global trends of sustainability pushes developing economies such as Vietnam to transform into green economy by 2030 (Abbas & Khan, 2023). However, based on International Labor organization (2020), 54% of organizations in Vietnam belong to manufacturing category and their vast consumption of unsustainable materials leads to massive environmental challenges. This also captures the attention of stakeholders and government that further pressures these firms to adopt sustainable practices to maintain environmental balance. According to Gupta & Barua (2018), innovative practices in this regard are helpful to limit the harmful impact, however, its adoption is quite challenging due to inconsistency in transition process throughout the region. It is also argued that the implementation of green practices in Vietnam is in slow-moving phase due to various barriers (Pham et al., 2023). In addition to this, awareness on green practices is also dubious in general public. Hence, it is imperative to assess the factors that ensure the success of green initiatives among Vietnam’s manufacturers In this regard, knowledge management practices are a critical focus, promising successful green initiatives. The collective agreement existing in literature outlines the essentiality of KM practices in case of green ventures as they aimed at facilitating organization with necessary environmental related knowledge that is further important for sustainable operations (Matuszewska-Pierzynka, 2021; Wang et al., 2022). According to literature, these practices allow firms to take maximum leverage on environmental knowledge related to associated compliance, technologies and appropriate practices. It is also argued that the effective management of knowledge, firms specially manufacturing can optimize their green performance and leverage green innovation. Additionally, mediating role of knowledge sharing behavior can’t be overlooked because knowledge sharing behavior promotes the dissemination of information among individuals that makes the adoption process of green practices much easier (Cera et al., 2022; Lin et al., 2024; Tien et al., 2023). Therefore, the present study holds great significance due to its emphasis on how green KM system ensures the successful implementation of green ventures in the domain of the Vietnamese manufacturing sector. The study investigates multiple facets of the GKM system, which includes green KC, KA, KAP, and KS. The study is significant due to its consideration of the impact of these facets of the GKM system on the success of green ventures through several innovative practices and green knowledge-sharing behavior in the organization. The study also adds significant contribution by extending its view on natural resource RBV perspective and knowledge-based dynamic capability perspective by explaining that organizations may have an option to utilize internal and external competencies in order to address environmental issues. This also shapes sustainable competitive advantage of firm which allows organizations to disseminate green information that is extremely challenging to be replicated. The latter part of the study is organized into four sections. Literature review covers the key concepts of variables along with the hypothesis development which are constructed in the light of previous literature. The literature review section also presents a theoretical model which supports the proposed framework of the study. In methodology section, data collection methods, sampling technique, study population and data analysis approaches are outlined briefly. Findings are also presented in following section where the economic meaning of findings are briefly elaborated. Finally, summary of key findings is concluded in the last section where limitation and implications are also discussed. Literature review Theoretical background Wernerfelt (1984) introduced the Resource-Based View (RBV) framework, which highlights the pivotal role played by an organization’s strategic resources and capabilities in shaping its competitive advantage. According to RBV, sustainable competitive advantages can be achieved when organizations possess resources that are unique, valuable, non-substitutable, and challenging for competitors to imitate. Recent research, exemplified by Amankwah-Amoah & Adomako (2021) underscores the value of timely and relevant knowledge acquisition from an organization’s resource network as a rare and valuable asset for achieving success. Atkoˇ ci¯ unien˙ e & Siudikien˙ e (2021) and Fernandes et al. (2022) further emphasize the strategic significance of recognizing knowledge as a valuable resource. The central focus of our study is based on the notion that green knowledge is crucial and strategic asset of green firm and it sparks the proactive participation of organization in environmentally friendly initiatives that uplift the overall environmental performance of firm. In this regard, Natural resource-based view, the extended version of RBV serves as a foundation to illustrate that how firms are able to manage their resources effectively while considering environmental paradigm. This version of RBV reflects on the pressure comes from stakeholders that push organization to take environmental measures in order to subdue the negative impact of wastages and emissions. On the other hand, the obligation also shapes firm existing practices with a great concern toward environment (Abbas, 2020a; Yodchai et al., 2022). Furthermore, the study also integrates NRBV perspective with the extended version of knowledge-based view. This view considers the dynamic capabilities of firm and according to Knowledge-Based Dynamic Capabilities (KBDCV), when precious knowledge and natural resources are combined together, they become a most critical asses of an organization. Hence, organizations may have an option to utilize internal and external competencies in order to address environmental issues. This also shapes sustainable competitive advantage of firm which allows organizations to disseminate green information that is extremely challenging to be replicated (Kaur, 2022). Moreover, when competitive advantage of firm is nourished in dynamic settings, it helps firms to embrace change and adjust their operations accordingly. It also boosts confidences to work on novel ideas that may shape business landscape. Based on afore-mentioned arguments, the study used integrated theoretical lens of RBV, NRBV and KBDC to explain the conceptual framework of the study. Based on the stated integrated perspective, it can be argued that resource-based view allows green ventures to reap benefits from distinctive and eccentric resources such as knowledge management practices to develop competitive edge and produce sustainability outcomes. Meanwhile, natural RBV provides such ventures a strategic thought-process that is necessary for them to recognize the significance of environmental resources to link knowledge management process with environmental initiatives. Knowledge based view in the context of dynamic capabilities extends the significance of proposed relationship by highlighting those dynamic capabilities of green ventures allows them to create, gather, share and implement knowledge to fulfill green consumer demands and address environmental challenges. In this regard, knowledge sharing behavior along with innovative M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 2 practices appear to be a bridge as they make sure that correct form of sustainable knowledge is being fostered to develop green products/ services leading to successful green ventures. Thus, the entire conceptual model illustrates that how knowledge as a unique resource and dynamic capabilities of firm shapes organizations to become innovative and achieve sustainable goals. Knowledge creation and successful green ventures Green knowledge creation effectively contributes toward the success of green ventures as it promotes innovation and concentrates on sustainable practices. The entire process of green knowledge management beings with the creation of novel ideas related to environment which are essential for navigating green innovation and sustainable performance of firm (Abbas, 2020b; Paraschiv et al., 2021). The focal point of majority of studies reveals that only those firms can successfully boost their environmental performance when they are capable of soaking up green knowledge and utilized effectively. In addition to this, it is also argued that green knowledge, a process of sharing, storing and acquiring information; can have a positive effect on knowledge driven leadership (Ahsan et al., 2020). Interestingly, this knowledge-driven leadership helps in promoting sustainability and innovation in organization which ensures green success. Studies highlight that green knowledge when integrated in business strategies, helps firms to incorporate their practices with sustainability-oriented framework (Shafi et al., 2022; Wang, 2019). Thus, establishing a vigorous knowledge base that promote green practices. This deliberate creation of green knowledge plays bigger role in success of green ventures as it simultaneously makes advancement in green innovation and sustainable practices (Pan et al., 2022). Further to discussion, studies postulate that green knowledge creation harbors knowledge sharing and collaboration across organizations which makes green ventures successful. By leveraging on green knowledge creation, firms are able to identify collective judgement to address complex environmental challenges (Orzes & Sarkis, 2019; Tiberius et al., 2021).. Besides, the concerted approach helps firms to develop a supportive eco-system for green venture to achieve long-term success. The inclusion of diverse perspective which is an outcome knowledge creation, creates more sustainable solutions leading to successful green ventures (Zhao, 2023). In addition to this, a robust network grounded in green knowledge creation also facilitates green ventures to gain access of new markets, find attractive funding opportunities and experience technological advancement that may lead to long-term success (Orzes & Sarkis, 2019; Tiberius et al., 2021). H1: Green Knowledge creation positively influences Successful green ventures. Knowledge acquisition and successful green ventures The sustainability literature significantly highlights a crucial role of knowledge acquisition in the success of green ventures. By reviewing conceptual and empirical evidences, it become easier to understand that how sustainable business outcomes are driven by knowledge acquisition. From theoretical point of view, there are several theories scholars come up with to explain the relationship between knowledge acquisition and successful green ventures (Banelien˙ e & Strazdas, 2023; Cheba et al., 2023). For instance, Guo (2023) argued that from resource-based view perspective, knowledge is a critical resource of firm which helps in building competitive advantage. Since, green knowledge represents eco-friendly practices and technologies, hence, it is viewed as a valuable source of a firm that makes organizations innovative. Therefore, acquiring green knowledge is crucial to achieve superior performance. Ahmed et al. (2022) also highlighted a critical aspect of knowledge, hence, categorizing it as a strategic source. According to authors, knowledge-based view conceptualizes the idea that knowledge acquisition and constant learning are two fundamental resources of firm that ensure the success of sustainable firms. Empirical literature also reveals that external knowledge acquisition makes firm innovative that would lead to long-term sustainability (Hud´ akov´ a et al., 2023). Study of Aamir et al. (2021) also argued firms engaged in collaborations and acquire relevant green knowledge, likely to achieve sustainable outcomes with success. In conclusion, success of green ventures is driven by collective efforts that are achieved through collaborative learning environment and diverse knowledge resources. Therefore, we hypothesize: H2: Knowledge acquisition positively influences Successful green ventures. Knowledge application and successful green ventures Knowledge application which is another crucial aspect of knowledge management positively affect green venture outcomes. Studies demonstrate that when knowledge is being utilized affectively it will allow firms to become more innovative to achieve sustainable outcomes. Study of Khan (2023) highlights that implementing green knowledge brings the best from individuals leading to log-term sustainability. This comprehensive understanding underscores that acquiring knowledge is not sufficient for organization, the effective implementation is the key to achieve desirable outcomes. Another study proclaims that green knowledge application within HRM may boost the performance of organization through significant advancements in existing operations (Tee et al., 2023). Hence, it can be hypothesized that: H3: Knowledge application positively influences Successful green ventures. Studies highlight the crucial role of effective knowledge storage mechanisms that are well-suited for green ventures to achieve green objectives (Maravilhas & Martins, 2019). Capitalizing on stored green knowledge allows firms to facilitate consumers needs by offering eco-friendly services. Resulting in successful green ventures (Chaithanapat et al., 2022). It is also argued that proper storage of knowledge allows firms to utilize valuable information on time to give better response to environmental threats. Stored knowledge also helps firms to give effective response to institutional and stakeholder pressures, leading to successful green ventures. This way firms’ innovative and absorptive capacity enhance; thus, it becomes easier to leverage on environmental information that is necessary to address environmental challenges (Tiwari, 2022). To discuss the argument further, organizations are also compelled to seamlessly integrate environmental considerations into their research and development initiatives, as underscored by (Abbas & Dogan, 2022) in response to the evolving demands of dynamic markets. These organizations must engage in activities that not only promote the production of high-quality products with minimal resource consumption but also yield benefits for both the environment and the company itself, aligning with the insights of (Song et al., 2022). Drawing from the preceding discussions surrounding Green Knowledge Management (GKM), Corporate Social Responsibility (CSR), and green innovation, the present research contends that firms equipped with a GKM system are strategically positioned to innovate in environmentally sustainable ways and successfully pursue their sustainable development objectives. H4: Knowledge storage positively influences Successful green ventures. Mediating role of innovation Through knowledge-based businesses, customers’ requirements, necessities, and expectations have steadily replaced the services and goods produced by traditional labor and creative organizations in recent years (Mizintseva & Gerbina, 2018). The key to organizational success is knowledge management, which also plays a big role in enabling M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 3 enterprises to generate novel products and services, expand into new markets, and become more sustainable. Authors concluded that organizations using knowledge management strategies were comparatively inventive and had superior long-term financial performance after doing analytic study on New Zealand enterprises. This study reveals that gaining industry knowledge, for instance, was crucial for promoting novelties that best met consumer wants. In their study of Spanish companies, L´ opez-Nicol´ as and Mero˜ no-Cerd´ an (2011) came to the conclusion that knowledge management strategy effects a sustainable firm performance by boosting its inventive capabilities and talents. Once an employee is prepared to absorb knowledge from and support other employees in developing new capabilities and skills, knowledge management, specifically knowledge sharing in a corporation, begins (Bonfiglio et al., 2019). Firms that actively engage in a continuous learning process exhibit a higher degree of success in delivering innovative products and services to their customers. Enhanced learning enables these firms to seize every opportunity to introduce products and services that align with the everevolving market demands. Firms that are equipped with relevant knowledge and market trends are able to realize the needs of consumers and stakeholders. In addition to this, the right amount of skills and capabilities also allows such firm to thrive by utilizing innovative practices that promise long-term sustainability. With robust learning mechanism, the efficiency of firms also increases which ensures success (Calantone et al., 2019; Mehdikhani & Valmohammadi, 2019). Study of Sanz-Valle et al. (2019) also established a link between knowledge management and technological innovation, emphasizing the need of constant learning to adopt innovative practices proactively. Similarly, another study demonstrate that organizations must have three abilities to be entered in innovative category; they are committed to learning, possess cultural and technological innovativeness and do have knowledge of market trends (Weerawardena et al., 2018). On the other hand, Chen et al. (2018) also highlights the significance of service innovation that shapes firms’ reputation in the society. However, with recent technological advancement, the predominant inclination of industries toward technological innovation, diverts their attention from service innovation (Den Hertog et al., 2010). It is also noteworthy that certain earlier research asserts the growing significance of service innovation even within manufacturing enterprises (Cheng & Krumwiede, 2019).s Den Hertog et al. (2019) offer a comprehensive definition of innovation in services as a "novel service experience or service solution encompassing one or more of the following dimensions: a fresh service concept, novel customer interactions, innovative value systems or business partnerships, novel revenue models, and pioneering organizational or technological service delivery systems." Furthermore, innovation in services can also manifest through the inventive amalgamation of existing services, technologies, personnel, and methodologies to cater to the needs of both existing and potential customers (Chen et al., 2019). Therefore, the hypotheses that have been formulated can be expressed as follows: H5: Innovative practices mediate the relationship between knowledge creation and successful green ventures. H6: Innovative practices mediate the relationship between knowledge acquisition and successful green ventures. H7: Innovative practices mediate the relationship between knowledge application and successful green ventures. H8: Innovative practices mediate the relationship between knowledge storage and successful green ventures. Mediation of green knowledge sharing behavior Knowledge sharing behavior is identified by scholars as a significant construct that happens to play effective role of mediator in organizational sustainability literature (Khan et al., 2019; Song et al., 2020). Since, the concept of knowledge management explains the series of activities such as creating, acquiring, storing and implementing it, therefore, it appears to be highly related to environmental sustainability of organization. In this regard, it can be deduced that success of green initiative generally relies on firms’ capability that how effectively it implements acquired knowledge and information (Cheng, 2019; Rennings & Zwick, 2020; Schoenherr & Swink, 2021). Empirical evidences also demonstrate that firms having knowledge sharing culture are more prone to conceptualize novel and innovative ideas that ultimately increase their innovative and absorptive capacity. Studies also highlight that promoting knowledge sharing environment multiplies the positive impact of green knowledge management because it provokes firms to exchange expertise and best practices that are truly a potential driver of firm’s success (Chen et al., 2019; Wu, 2019). It is also argued that knowledge sharing is a vital form of bridge that allows firm to convert knowledge resources into tangible outcomes, leading to successful green outcomes. The debate highlights that knowledge sharing behavior is not simply an auxiliary process, it serves as a catalyst to create the bridge between green knowledge management and successful green venture by increasing environmental responsibility and fostering innovative capabilities (Arfi et al., 2018; Srinivasan & Swink, 2018). Therefore, we hypothesize that: H5: Knowledge sharing mediates the relationship between knowledge creation and successful green ventures. H6: Knowledge sharing mediates the relationship between knowledge acquisition and successful green ventures. H7: Knowledge sharing mediates the relationship between knowledge application and successful green ventures. H8: Knowledge sharing mediates the relationship between knowledge storage and successful green ventures. Methodology Research strategy and sampling of target population The researcher has followed the aligned conceptions from the positivism philosophy, a deductive approach of using the generalized theory concepts to synthesize specific designed hypotheses, and used the primary data quantitative research strategy for data collection (Saunders et al., 2007). The researcher has targeted the employees of the manufacturing firms working in various organizational settings within the country boundary of Vietnam. The targeted population has been defined as the sub-group of the whole population consisting of the same properties in the aspect of perception (Memon et al., 2020). The present study used cross-sectional research design to explore the assess the stated relationship. Furthermore, the study used non-probability purposive sampling technique to select and assess respondents. The reason for choosing this technique as it helps in selecting those respondents that truly represent sample population having particular characteristics perfectly aligned with research objectives. The selected sampling technique ensures researchers that selected sample is aware of terms such as green knowledge, knowledge sharing behavior, innovative capabilities, entrepreneurship etc. An inclusion criterion was specifically developed for present study to identify desired sample population. Firstly, it is to make sure while selecting respondents that they must have minimum 3-year experience in a company which adopts green practices. Secondly, researchers made sure that sample chosen for the study actively involves in green knowledge management and innovative practices. In addition to this, only those employees were considered who hold critical position in the company related to sustainability and knowledge management initiatives. The study also developed a three-step procedure to reach out participants; identification of industry, preliminary contact, and ultimate selection. Pertaining to industry identification, only those manufacturing firms were considered who are familiar with green knowledge management practices and largely known for green M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 4 innovative practices. The identification was done with the help of industry reports and other relevant sites. Researchers prepared a brief list of potential respondents based on inclusion criteria and they were approach through professional networks. Lastly, participants were finalized that were perfectly aligned with inclusion criteria and agreed to participate in the study without any pressure. Further to discussion, the study used Daniel Soper calculator to derive the sample size of the study as Soper (2024) argued that sample size for SEM can be determined through number of observed and latent variables, anticipated effect size and significance level. Based on the criteria, the sample size drawn for the study was 180. However, for better generalization, the study collected data from 300 employees. This helped researchers to handle potential loss in case of partial responses. After collecting the responses, the study used data cleaning process by removing incomplete surveys, identifying outliers and assessing redundant entries. While data cleaning process, 15 responses were omitted because they were incomplete. Instrumentation and measurement of the variables The researcher has used all the scales of the variables from authentic and empirically evaluated study measurements. The researcher has used the online and self-administered mediums for the collection of primary data. For the measurement of different knowledge practices, the researcher encountered a study that used all the sub-constructs of knowledge management altogether in one framework and measured knowledge acquisition with the help of 5 items, the knowledge creation with the help of 5 items, knowledge storage by 5 items, and knowledge application by using 6 items and all scale items have reliable Cronbach alpha values (Yu et al., 2022). The mediating variable of green knowledge sharing was adopted from a study that used 5 items for the measurement of green knowledge sharing with the Cronbach alpha value of 0.887 (Zhang et al., 2021). Next, the second mediating variable of the study the innovative practices was measured by using a 10-items scale (Wang et al., 2022) and primarily adopted the scale from (Kam-Sing Wong, 2012). In the end, the dependent variable of successful green ventures was measured in this study on 5 items used by a very recent study and highlighted the reliability and validity of the scale items with 0.927, and AVE of 0.719 respectively (Jinliang et al., 2023). Along with the main body questions in the questionnaire, the researcher has also asked some demographical questions from the respondents and the most common questions include age, gender, education, work experience, and type of job. Data analysis techniques and ethical considerations The researcher has used the SPSS software for initial screening including missing values, outliers, and normality of the data, items, and variables. along with it, the researcher has run the advanced testing of PLS-SEM comprised of two steps one of which includes reliability and validity computation and the second step of structural equational modeling in which high-quality steps of two-stage approach and bootstrapping have been used (PLS, 2023; SmartPLS, 2023). Further, the researcher has considered all the ethical considerations while conducting this research and has collected all the data with the voluntary participation of respondents, has ensured the anonymity and the confidentiality of the personal information and has compiled all the results with no personal inference and biases, and yes originally depicted the viewpoint of the respondents in discussion (Scribber, 2023). The following table shows the description of the gathered scales, their sources and the number of the items. Variable Name Symbol No of items Source Knowledge creation KC 5 (Yu et al., 2022). (continued on next column) (continued) Variable Name Symbol No of items Source Knowledge acquisition KA 5 (Yu et al., 2022). Knowledge storage KST 5 (Yu et al., 2022). Knowledge application KAP 6 (Yu et al., 2022). Knowledge sharing KS 5 (Yu et al., 2022). Innovative practices IP 10 (Kam-Sing Wong, 2012) Successful green ventures SGV 5 (Jinliang et al., 2023) Findings Internal consistency reliability In order to evaluate the reliability of different variables the researcher has employed internal consistency reliability. According to Surucu and Maslakci (2020), internal consistency reliability is often referred to as a “test retest” approach because in this a same test is performed several times after a particular time frame and then there obtained results are compared, if the test yield similar results again and again it indicates the construct are reliable. Reliability is assessed through Cronbach alpha. According to (Hair et al., 2011), the value of α should be more than 0.7 to establish reliability. Results of internal consistency reliability is given in table 1 below. The value of α for IP, KA, KAP, KC, KS, KST and SGV is 0.91, 0.80, 0.88, 0.89, 0.91, 0.87 and 0.83, respectively. All the obtained values are above 0.7, thus the current data set is reliable. Outer loadings After the examination of internal consistency reliability for each variable, the researcher has analysed outer loadings (indicators reliability). The estimated associations presented in the reflective measurement model of a study is termed as outer loadings (Modak et al., 2023). According to Kamis et al. (2020), the value of outer loadings ranges between 0 and 1, however 0.6 is the cut-off value. The results of outer loadings are presented in table 2. In this table, only those factors of the variables are included whose indicator reliability is greater than 0.6. For instance, the factors included for measurement of indicator reliability of IP were IP4, IP5, IP6, IP7, IP8, I9, and IP10, for KA were KA1, KA2, KA3, and KA5, for KAP were KAP1, KAP2, KAP3, KAP4, KAP5 and KAP6, for KC were KC1, KC2, KC3, KC4, and KC5, for KS were KS1, KS2, KS3, KS4, and KS5, for KST were KST1, KST2, KST3, KST4 and KST5, and lastly for SGV were SGV1, SGV2, SGV3, SGV4 and SGV5. Convergent validity To measure the dataset’s true reliability, convergent validity was determined. It is measured with two indicators, “Composite Reliability Table 1 Internal consistency reliability. α IP 0.916 KA 0.802 KAP 0.884 KC 0.894 KS 0.915 KST 0.878 SGV 0.837 Note: “KA=Knowledge acquisition, KAP=Knowledge application, KC= Green Knowledge creation, KS= Knowledge Sharing, KST=Knowledge Storage, SGV=Successful green ventures, IP=Innovative practices” M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 5 (CR) and Average Variance Extracted (AVE).” In the view of Hanafiah (2020), CR must be greater than 0.7, and AVE should be more than 0.5 to ensure the dataset is valid. Results of convergent validity is provided in table 3, the table indicates that values of CR for all observed variables i. e., IP, KA, KAP, KC, KS, KST, and SGV are above 0.7, and their AVE values are also above 0.50, thus the dataset is valid. Discriminant validity Discriminant validity analyses how closely a measurement test measures the intended concept. It further specifies that particular constructs are unrelated that must not be theoretically relevant to one another (Ronkko & Cho, 2022). In current study, researcher has assessed discriminant validity by employing two approaches i.e., “HTMT Criterion and Fornell Larcker’s (1981) criterion.” HTMT HTMT is a novel approach to analyse discriminant validity. To ensure that discriminant validity is established in dataset, the HTMT value should be distinguished from 1 (Rasoolimanesh, 2022). According to Ab Hamid et al. (2017), if the resultant value of HTMT of all the observed variables are less than 1, discriminant validity is said to be existed. Results of HTMT is given in table 4. As all the values presented in table are below 1, it confirms discriminant validity. Fornell-Larcker (1981) criterion According to Fornell-Larcker (1981) criterion, the value of correlation between variables and any other variables must be lesser than the square root of AVE of a variable (Hair Jr et al., 2021). The results of Fornell-Larcker are presented in Table 5, the results show the existence to discriminant validity through Fornell-Larcker approach. Measurement model The measurement model of present study is shown in Fig. 1 and Fig. 2 below. In this model, there are four independent variables including green knowledge creation with 5 items, knowledge acquisition with 5 items, knowledge application with 6 items and knowledge storage with 5 items. Moreover, there are two mediating variables including innovative practices with 10 items, and knowledge sharing with 5 items. Lastly, one dependent variable that is successful green ventures with 5 items. SEM analysis In this study, SEM was employed to analyse the direct and indirect path analysis, and for assessing the hypotheses significance bootstrapping approach was utilized, as this approach is useful for yielding accurate results. The results of path analysis are shown in table 6 in which the thumb of rule for the hypothesis to get accepted is that its level of significance must be less than 0.05, however, some of the hypotheses get accepted at p-value 0.10 as well. In this study, there were 4 direct and 8 indirect hypotheses. The results shown indicated that the relationship between KST and SGV was accepted as its p-value is 0, and t-statistics 4.502. However, all other direct hypotheses were rejected because they did not fall on the criterion set for significance. Here 0 pvalue suggests a strong statistical significance between variables. The tstatistic which is 4.502 further supports the significance of relationship, outlining that knowledge sharing storage positively affect successful green ventures. This means that dedication of firms toward knowledge storage mechanism leads to success of green ventures. Therefore, when firms successfully manage their stored knowledge to be utilized for sustainable purposes, they likely to gain more benefits and experience success in their green initiatives. The rejection of other direct hypotheses indicate that they failed to meet the significance criteria, highlighting that other dimension of green knowledge management such as knowledge acquisition, knowledge application, knowledge creation did not reveal a significant impact in the given dataset. This articulate that not all the dimensions of green knowledge management can be a key to successful green ventures. This also implies that depending on context, resources and efforts should be devoted to particular dimensions of knowledge management rather than focusing on their collective impact. From Table 6, it can be observed that innovative practices do not mediate the relationship between knowledge acquisition, knowledge application and successful green ventures because the significant value is greater than 0.05. This indicates that innovative practices did not prove to be facilitator in their current form to make acquired knowledge useful for the success for green ventures. The absence of mediation also highlights that innovative practices even being effective often Table 2 Outer loadings. IP KA KAP KC KS KST SGV IP10 0.721       IP4 0.842       IP5 0.851       IP6 0.855       IP7 0.882       IP8 0.83       IP9 0.728       KA1 0.862      KA2 0.818      KA3 0.785      KA5 0.696      KAP1 0.783     KAP2 0.834     KAP3 0.795     KAP4 0.818     KAP5 0.797     KAP6 0.731     KC1 0.831    KC2 0.857    KC3 0.862    KC4 0.829    KC5 0.811    KS1 0.872   KS2 0.877   KS3 0.868   KS4 0.857   KS5 0.843   KST1 0.762  KST2 0.858  KST3 0.888  KST4 0.807  KST5 0.784  SGV1 0.711 SGV2 0.877 SGV3 0.88 SGV4 0.733 SGV5 0.685 Note: “KA=Knowledge acquisition, KAP=Knowledge application, KC=Green Knowledge creation, KS=Knowledge Sharing, KST=Knowledge Storage, SGV= Successful green ventures, IP=Innovative practices” Table 3 Convergent validity. Cronbach alpha Composite reliability Average variance extracted (AVE) IP 0.921 0.934 0.669  KA 0.823 0.873 0.628  KAP 0.898 0.911 0.638  KC 0.897 0.922 0.702  KS 0.915 0.936 0.745  KST 0.878 0.912 0.674  SGV 0.848 0.886 0.611  Note: “KA=Knowledge acquisition, KAP=Knowledge application, KC=Green Knowledge creation, KS=Knowledge Sharing, KST=Knowledge Storage, SGV= Successful green ventures, IP=Innovative practices” M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 6 implemented improperly when align with knowledge acquisition and application. Further, the negative coefficient of indirect path highlights that sometimes-innovative practices have an adverse impact in the form of barriers that may subdue the benefits of knowledge acquisition and application. There could be several reasons for it. For example, if innovative practices are not properly matched with strategic objectives of green ventures, chances are less to get benefit from acquired knowledge. Misallocation of resource devoted to IP might damage the potential benefit of knowledge acquisitions. Also, if innovative practices are implemented poorly then organizations may face operational challenges which converse the relationship of KA and SGV. In addition to this, innovative practices often deflect green ventures from other useful resources including human capital, time etc; which are also crucial for the success of green firms. Besides, additional complexities in the form of change resistance, bureaucratic challenges create difficulties for green ventures to implement innovative practices properly. Particularly in Vietnamese context, it can be explained that if green firms choose Table 4 HTMT. Note: “KA=Knowledge acquisition, KAP=Knowledge application, KC=Green Knowledge creation, KS=Knowledge Sharing, KST=Knowledge Storage, SGV= Successful green ventures, IP=Innovative practices” Table 5 Fornell-Larcker. IP KA KAP KC KS KST SGV IP 0.818       KA 0.341 0.792      KAP 0.212 0.361 0.794     KC 0.482 0.119 0.102 0.838    KS 0.641 0.205 0.266 0.665 0.863   KST 0.525 0.254 0.195 0.395 0.427 0.821  SGV 0.562 0.159 0.182 0.363 0.508 0.559 0.782 Note: “KA=Knowledge acquisition, KAP=Knowledge application, KC=Green Knowledge creation, KS=Knowledge Sharing, KST=Knowledge Storage, SGV= Successful green ventures, IP=Innovative practices” Fig. 1. Measurement Model. M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 7 technologies that are either costly or not aligned with domestic market conditions; their resources might not be useful their green success journey. Also, operational disruption can also be occurred if individuals do not possess critical skills which brings negative effect on the success of green ventures. Further to discussion, innovative practices proved to be a significant mediator in case of knowledge creation and knowledge strategies as pvalues are less then 5% and t-values are greater than 1.96. Innovative practices fully mediate the relationship of knowledge creation with SGV whereas it partially mediates the relationship of knowledge storage with SGV. This implies that knowledge creation needs supportive mechanisms to influence SGV positively. The presence of full mediation in that case confirms that knowledge creation is effective when it is utilized for innovation purposes. This significant indirect path shows that effectively transforming created knowledge into innovative actions is substantial for green ventures. To explain it further, it can be illustrated that creating knowledge does not guarantee green success, however, when it is applied through the lens of innovation, it adds greater value to the firm. Results also imply that knowledge effectively stored and retrieved by firms facilitate in achieving green goals. Besides, it should also be implemented along with innovative practices to fully realize the collective potential benefits on green success. Table 6 also explains that knowledge sharing behavior does not mediate the association of KAP and KA with SGV. The insignificant indirect path values suggest although these aspects of knowledge management are important, however, their impact in the context of green venture success is not straight forward. Therefore, the relationship is not mediated by knowledge sharing behavioral as well. Furthermore, it was found that KS fully mediates the association between KAP and SGV (p-value 0.066, t-statistics 1.84), and partially between KST and SGV (p-value 0.013, t-statistics 1.84) and between KC and SGV (p-value 0.006, t-statistics 1.84). Discussion and conclusion Discussion of key findings The researcher has designed a comprehensive model with the association between green knowledge-based practices and successful green ventures in the section of the literature and has empirically evaluated them with the help of the PLS-SEM technique. After running the main test of hypotheses testing in the Smart PLS, the researcher has revealed some mixed results. The researcher has explored the significant direct and indirect impact of knowledge creativity and knowledge storage on the successful green ventures through knowledge sharing and innovative practices. As well as the study has illustrated the significance of knowledge application for the success of green practices of manufacturing sector firms. For the empirical support and validation of the encountered results, the researcher has searched and cited relevant, appropriate and sufficient literature studies. To verify the significance of knowledge management practices, a study was found that investigated all 4 types of knowledge management practices in increasing organizational performance and their data analysis revealed support for their assumed relationship and verified the incumbency of the KM practices including knowledge sharing, creativity, and storage in accelerating the performance level (Migdadi, 2022). Fig. 2. SEM. Table 6 Hypotheses Testing. Original sample Sample mean Standard deviation T statistics P values KA ->SGV 0.037 0.036 0.053 0.693 0.489 KAP ->SGV 0.057 0.053 0.055 1.038 0.301 KC ->SGV 0.015 0.014 0.074 0.206 0.837 KST ->SGV 0.312 0.304 0.067 4.502 0.000 KA ->IP -> SGV -0.005 -0.004 0.011 0.437 0.662 KC ->IP -> SGV 0.049 0.05 0.019 2.591 0.010 KAP ->IP ->SGV -0.003 -0.002 0.012 0.217 0.828 KST ->IP ->SGV 0.082 0.084 0.026 3.174 0.002 KAP ->KS ->SGV -0.025 -0.022 0.011 1.844 0.066 KST ->KS ->SGV 0.049 0.049 0.019 2.505 0.013 KA ->KS -> SGV -0.002 -0.002 0.012 0.167 0.867 KC ->KS -> SGV 0.094 0.094 0.034 2.771 0.006 Note: “KA=Knowledge acquisition, KAP=Knowledge application, KC=Green Knowledge creation, KS=Knowledge Sharing, KST=Knowledge Storage, SGV= Successful green ventures, IP=Innovative practices” M. He et al. Journal of Innovation & Knowledge 9 (2024) 100618 8