39 Organizacija, V olume 57 Issue 1, February 2024 Research Papers 1 Received: 1st September 2023; Accepted: 21st January 2024 Creating Dynamic Learning Capability in Learning Framework through Strategic Alliance Febri Nila CHRISANTY 1 , Riani RACHMAWATI 1 , Prijono TJIPTOHERIJANTO 1 1 University of Indonesia, Faculty Economics and Business, Depok, Indonesia, febrinilac@yahoo.com (corresponding author) Background and Purpose: The changing ecosystem demands improvement in a company’s capabilities through its learning framework and respective dimensions. Using empirical testing, the purpose of this research is to gain a better understanding of the creation of dynamic learning capability through strategic alliances in the learning frame - work. Methodology: The data were collected via an online survey of 78 strategic alliances of a public institution. The structural equation model (SEM) was used to test the proposed model. Finding: Dynamic learning capability positively and significantly affects strategic alliance performance in a learning framework that comprises relationship capital, surfacing, joint learning structure, and knowledge acquisition dimen- sions. Conclusion: This research finds that all constructs in the learning framework (relationship capital, surfacing, joint learning structure, and knowledge acquisition) create dynamic learning capability, which has a significant effect on strategic alliance performance. Each construct within the learning framework (relationship capital, surfacing, joint learning structure, and knowledge acquisition) was empirically tested and can create the dynamic learning capability that contributes to the strategic alliance’s performance, notably within the business learning domain. Keywords: Strategic alliances, Learning framework, Dynamic learning capabilities, Strategic alliance performance DOI: 10.2478/orga-2024-0003 1 Introduction One of the 10 most significant shifts facing organisa- tions today is closing the capability chasm (McKinsey, 2023). In a survey of more than 2,500 business leaders around the world, only 5% of the respondents stated that their organisations had the capabilities they needed (Mc Kinsey, 2023). Related to Ahmad, Omar, and Quoquab (2019), a company’s sustainability depends on its cor- porate sustainable longevity, which in turn relates to the company’s resources: financial strength, vision and strate- gy, customer orientation, internal capabilities, and learning and growth. This condition indicates that most companies have some level of need to fulfil their company’s capabili- ty to sustain the competitiveness of their business. Accord- ing to Haapane, Hurmelinna-Laukkanen, and Puumalainen (2020), dynamic capability is an organisation’s capacity to create, extend, or modify its resource base, directing managers with dynamic managerial capabilities. Dynam- ic capabilities are recognised as specialisation and rapid competitive responses through the maintenance of asset alignment capabilities. In this way, collaborating firms can combine assets to create and deliver value to customers, which can be regarded as action by the company to adapt 40 Organizacija, V olume 57 Issue 1, February 2024 Research Papers its process or acquire knowledge (Furnival, Boaden, & Walshe, 2019). Gonzales-Perez and Ramirez-Montoya (2022) stated that three types of competencies are required in the mod- ern-day workplace: learning skills, literacy skills, and life skills. Learning skills consist of creativity and innova- tion, critical thinking, problem-solving, communication, and collaboration. Pereira and Romero (2017) found that skill development is an essential key factor in adopting and implementing the Industry 4.0 framework. Howev- er, Industry 4.0 is often misinterpreted and focuses only on the technology perspective while in reality, companies must also change their organisational structures and cul- tures (Schuh, Dumitrescu, Kruger, & ten Hompel, 2020). This demonstrates that technology relates to technical ca- pability and the variables impacted within its ecosystem. Therefore, Industry 4.0 will create automation tasks that will require professional employees to have the relevant capability to derive the maximum benefits from the new technology trends and business opportunities, including the need for suitable learning methods. Education 4.0 also differs from traditional education as it relies on digital strategies, digital security, and proper infrastructure (Gon- zales-Perez & Ramirez-Montoya, 2022). Industry 5.0 fo- cuses on concepts of sustainability, bioeconomy, and a col- laborative environment of technology and human beings that can create a resilient industry and incorporate human social values (Frederico, 2021; Sindhwani et al., 2022). In Industry 5.0 (education and training research themes), universities must incorporate transdisciplinary education, cognitive skills, and social and environmental aspects, supported by digital technologies (Borchardt et al., 2022). Universities must therefore also have multi-education sup- ported by digital technologies to support lifelong learning for employees. Learning can be interpreted as a process of repetition and experimentation that improves task execution and enables the quicker identification and obtaining of new product opportunities from the organisational internal and external environment (Rashidirad & Salimian, 2020). In- ternal learning includes multifunctional employee train- ing, knowledge database maintenance, and knowledge sharing, while external learning occurs mainly through relationships with customers and suppliers and interna- tional joint ventures that can modify the business direction (Rashidirad & Salimian, 2020). The internal or external learning environment can be represented as the learning framework, which in turn comprises four elements: rela- tionship capital, surfacing, joint learning structures, and knowledge acquisition (Morrison & Mezentseff, 1997). Relationship capital concerns unique relationships on a personal or company level built by mutual trust, respect, and friendliness as well as closely interactive relationships characterised by mutual respect and trust between parties (Paul, Robert, Benn, & Kenneth, 2006). Surfacing con- cerns how people learn to surface, challenge, and adapt mental models related to assumptions, images, and gen- eralisations to understand the world and the actions they will take (Morrison & Mezentseff. 1997). A joint learning structure is a structure for sharing knowledge between the company and its strategic partner (Galeazzo, Furlan, & Vinelli, 2016). The final element is knowledge acquisition, in which external knowledge acquisition is incorporated into a direct market exchange and cooperation agreement or strategic alliance (Ortiz, Donate, & Guadamillas, 2018). In the context of learning, collaborative learning is the process of sharing knowledge, information, and resources in supply chains (Rupčić, 2020). Cooperation agreements or strategic alliances are the methods used to acquire complex and specialised knowledge, frequently requiring learning development (Savino, Messeni Petruzzelli, & Al- bino, 2017). In other words, a company’s capability can be developed with internal resources through their learning process and by external collaboration, such as strategic al- liances, to obtain new and relevant knowledge. Many pre- vious studies have discussed the definition of strategic alli- ances. Yoshino and Rangan (1995) explained that strategic alliances involve at least two partner firms and once the alliance is formed, it may constitute a separate legal enti- ty. Types of alliances include joint ventures, joint research development, hierarchical relations, cooperatives, equity investments, subcontractor networks, consortia, strategic cooperative agreements, cartels, action sets, franchising, licensing, industry standards groups, and market relations. The cooperative agreements can help companies improve their learning frameworks efficiently (both financial and non-financial). Strategic alliances also include universi- ty partnerships, joint ventures (equity partnerships), and non-equity partnerships (Fey & Birkinshaw, 2005). In summary, strategic alliances in the learning environment can make continuing contributions to the performance of assigned tasks and can create dynamic capability. All companies must improve their performance and innovate to remain competitive and sustainable (Hi- jal-Moghrabi, Sabharwal, & Ramanathan, 2020). This applies equally to public institutions. The public sector’s competitive advantage lies in improving public servic- es and eliminating inefficiencies and waste. Concerning innovation, it should also focus on increasing value for the public through widespread improvements in service performance and governance (Popa, Dobrin, Popescu, & Draghici, 2011). The public sector’s innovation capacity thus lies in its ability to improve services that enhance the value of public institutions and differentiate them from others by adapting to social changes and the needs of cit- izens and stakeholders (Popa et al., 2011). Nevertheless, the adoption of technology to create a digital government poses certain challenges (Chen & Hsieh, 2014). These relate to three significant domain aspects: technology or technical, institution or organisation, and people. Regard- 41 Organizacija, V olume 57 Issue 1, February 2024 Research Papers ing the people aspect, the challenges are the culture of so- ciety, the digital divide, legal issues, the economy of so- ciety, human resources, public officials and citizens being slow to adapt, a lack of skill and expertise, leadership, and reliability (Arief, Wahab, & Muhammad, 2021). To sum- marise, the challenge in digital government concerns the need for technology-savvy talent created through devel- opment and human capital transformation. Furthermore, companies must consider reactions within the organisa- tion, such as the organisational readiness for change and employee performance, including counterproductive work behaviour (Chrisanty, Gunawan, Wijayanti, & Soetjipto, 2021). Previous research has indicated that each construct in the learning framework can create dynamic capability. However, there has not been a complete learning frame- work comprising all the learning constructs (relationship capital, surfacing, joint learning structure, and knowledge acquisition) in the context of creating dynamic learning capability, especially in a learning area. This study there- fore empirically examines the effect of a complete learning framework on dynamic learning capability and strategic alliance performances. This study was conducted in public institutions in Indo- nesia. Public institutions must maintain their competitive advantage by protecting their good reputation, innovation capability, and efficiency. Many have already developed dynamic capabilities through domestic and international strategic alliances and implemented various learning and research area programmes as part of their strategic allianc- es with diverse organisations. However, the current prior- ity is the on-point target accomplishment of the strategic alliance programme. Accordingly, this research attempts to answer a research question: How does dynamic learn- ing capability affect the strategic alliance performance in a complete learning framework (relationship capital, surfac- ing, joint learning structure, knowledge acquisition)? The study is divided into five sections. The first sec- tion presents the conceptual framework. The methodolo- gy is then described in the second section. The empirical results are explained in the third section. The fourth sec- tion discusses the research results. Finally, the research is concluded in the fifth section, alongside some managerial recommendations, limitations of the study, and potential future research avenues. 2 Dynamic Learning Capability in a Learning Framework Relationship capital concerns the unique relationships on a personal or company level that are built on mutual trust, respect, and friendliness in addition to closely in- teractive relationships featuring mutual respect and trust between parties (Paul et al., 2006). The process of learn- ing between alliances can indirectly influence alliance performance through trust and relationship commitment (Shan, Dan, & Qiu, 2018). The relationship benefits in- volve reducing transaction and supervision costs through information and risk-sharing (Shan et al., 2018) and ac- quiring unique knowledge (Lenart-Gansiniec, 2016). The formal and informal socialisation mechanism impacts re- lational capital in a way that increases the supplier rela- tionship outcomes (Cousin, Handfield, Lawson, & Peters- en, 2006). Building a learning relationship concerns the management’s ability to create a learning vision that can then be shared throughout the relationships. This ability derives from the formation of a new management style in which coordination is prioritised over a hierarchical approach. Previous research identified that commitment, coordination, trust, and interaction frequency have a sig- nificant impact on inter-organisational relationship perfor- mance (Nguyen, Mai, & Nguyen, 2021). The leader of a company acts as a coordinator (Osterberg, 1993). A strong management style within learning alliances is important as it extends across the relationship (Morrison & Mezent- seff, 1997). This indicates that learning relationship capi- tal depends on the management coordination role via the relationship with strategic alliances. Therefore, while re- lationship capital has an impact on dynamic learning capa- bility and strategic alliance performance, it has never been empirically tested in conjunction with other constructs in the learning framework, namely surfacing, joint learning structure, and knowledge acquisition, especially in the learning area. Correspondingly, we propose that: H1: Relationship capital is positively related to dy- namic learning capability. The most significant learning in an organisation in- volves changing mental models (Senge, 1992). Surfacing, meanwhile, relates to how people learn to surface, chal- lenge, and adapt the mental models related to assumptions, images, and generalisations in order to understand the world and the actions they will take (Morrison & Mez- entseff, 1997). Yue, Hua, and Quan (2018) defined the learning process of an alliance as the acquiring, encoding, sharing, and internalising of proprietary technology or information related to the alliance and alliance manage- ment. The translation of alliance managerial information or proprietary technology from individuals into implicit or explicit information refers to information acquisition (Yue, Hua, & Quan, 2018). Information acquisition will assist the company in retaining its knowledge and sharing it with the next manager. Information encoding refers to the creation and use of information objects or resources, such as alliance criteria, lists, or manuals, to take action or decisions regarding a future alliance (Yue et al., 2018). Meanwhile, the organisation’s process of exchanging and sharing alliance management knowledge with individuals in related interior departments within the enterprise refers to information sharing (Yue et al., 2018). Thus, the shar- ing forum becomes a place where knowledge is accessible 42 Organizacija, V olume 57 Issue 1, February 2024 Research Papers and can be exchanged and disseminated through dialogue between a company and its strategic partner. Information internalisation refers to the organisation’s process of ex- pediting alliance proprietary technology owned by the organisation to become individual information (Yue et al., 2018). Therefore, surfacing has an impact on dynam- ic learning capability and strategic alliance performance. However, it has never been empirically tested alongside the other constructs in the learning framework, namely re- lationship capital, joint learning structure, and knowledge acquisition, particularly in the field of learning. Corre- spondingly, we propose that: H2: Surfacing is positively related to dynamic learning capability. A joint learning structure is an arrangement for sharing knowledge between the company and its strategic partner. Based on Galeazzo, Furlan, and Vinelli (2016), organisa- tional learning infrastructure has three dimensions: stra- tegic alignment, teamwork for problem-solving, and the goals management system. Strategic alignment, as the first dimension, improves the products and processes by enhancing the company’s ability. It involves exploiting and synergising the company’s competencies, technolo- gy, and innovation and continuously stimulating the new knowledge available to functions and cross-learning. As such, strategic alignment aims to create synergies between the company and its strategic partner by exploiting both resources and new knowledge. The second dimension is teamwork for problem-solving. This relates to employees working in teams to solve problems since they have a mu- tual understanding and a common language, and improve the organisational climate (Galeazzo et al., 2016). Team- work will create the same objective and goal and make it easier for a company and its strategic partner to solve problems through collaboration. The third dimension is the goals management system. This relates to how the com- pany shapes decisions and actions through rewards and incentives to achieve the organisation’s goals (Galeazzo et al., 2016). The company must create a system that will result in the realisation of its goals by influencing the de- cisions and actions of its employees. Therefore, the joint learning structure has an impact on dynamic learning ca- pability and strategic alliance performance but has never been empirically tested alongside the other constructs in the learning framework: relationship capital, surfacing, and knowledge acquisition, notably within the learning domain. Consequently, we propose that: H3: Joint learning structure is positively related to dy- namic learning capability. Ortiz, Donate, and Guadamillas (2018) grouped ex- ternal knowledge acquisition into direct market exchange and cooperation agreements or strategic alliances. These groups were developed in line with the characteristics and goals of knowledge acquisition. The quickest acquisition method is direct market exchange (contracting) through external R&D and direct acquisition. Examples of direct acquisition include licensing and consulting, recruitment of staff with specific knowledge, and company acquisition (Davenport & Prusak, 1998). Cooperation agreements or strategic alliances are methods for the acquisition of complex and specialised knowledge, frequently requir- ing learning development (Savino et al., 2017). Specific examples of strategic alliances include university part- nerships, joint ventures (equity partnerships), non-equity partnerships (Fey & Birkinshaw, 2005), and cooperation agreements with competitors, customers, and suppliers (Arvanitis, Lokshin, Mohnen, & Wo¨rter, 2015). As such, knowledge acquisition has an impact on dynamic learning capability and strategic alliance performance, although it has never been empirically tested in connection with the other constructs in the learning framework, namely rela- tionship capital, surfacing, and joint learning structures, particularly in the field of learning. As a result, we propose that: H4: Knowledge acquisition is positively related to dy- namic learning capability. 3 Dynamic Learning Capability Creating Strategic Alliance Performance Dynamic learning capability concerns a company’s ability to address opportunities by proposing new products or services (Matysiak, Rugman, & Bausch, 2018). Learn- ing is interpreted as a process of repetition and experimen- tation that improves tasks and enables the quicker identifi- cation and obtaining of new product opportunities from the organisational internal (Teece, Pisano, & Shuen, 1997) and external environments (Lin & Wu, 2014). Internal learning includes multifunctional employee training, knowledge database maintenance, and knowledge sharing, while ex- ternal learning is mainly conducted through relationships with customers, suppliers, and international joint ventures (Lin & Wu, 2014) that can modify the business direction (Lavie, 2006). A company becomes more competent in as- similating external knowledge in similar fields due to pos- itive feedback between experience and learning (Zhou & Wu, 2010). The learning capability has a positive effect on the company’s ability to create value (Rashidirad & Sal- imian, 2020). While all of the above-cited literature has included empirical studies on dynamic learning capability and strategic alliance performance alone, these have never been empirically tested alongside the other constructs in the learning framework, especially in the field of learn- ing. As such, and to answer the research question “Does dynamic learning capability correlate to strategic alliance performance?”, the following hypothesis is proposed: H5: Dynamic learning capability is positively related to strategic alliance performance. 43 Organizacija, V olume 57 Issue 1, February 2024 Research Papers It is necessary to measure the performance of the stra- tegic alliance as the company will need to evaluate the programme and improve the critical areas. Alliance per- formance can be measured using two methods. First, the objective method by analysing secondary data on the focal company over a period (Glaister & Buckley, 1998) and second, the subjective method, by asking the alliance man- ager or person directly involved in handling the day-to-day alliance matters (Dhaundiyal & Coughlan, 2020). 4 Method 4.1 Measures Variable measurements were adapted from the litera- ture on the respective variables. The measure for strate- gic alliance performance was adapted from Dhaundiyal and Coughlan (2020). The measure for dynamic learning capability was adapted from Rashidirad and Salimian (2020). The relationship capital measure was adapted from Nguyen, Mai, and Nguyen (2021), while that for surfac- ing was adapted from Yue et al. (2018). The measure for joint learning structure was adapted from Galeazzo et al. (2016), and the measure for knowledge acquisition was adapted from Ortiz et al. (2018). The response for each item was measured using a seven-point Likert scale rang- ing from (1) “strongly disagree” to (7) “strongly agree”. The questions were tailored to fit the research area, which is the public institution, and tested via a wording test by Figure 1: Research Mode three representative respondents and customised based on their inputs. After the customisation, the questions were tested via a pre-test with 35 respondents whose profiles matched that of the target unit analysis. The pre-test re- sults confirmed the reliability and validity of the questions. No further changes were made to the questions after the pre-test was conducted; therefore, the final version, as pre- sented in the appendix, was distributed to all respondents. Table 1 shows the constructs employed in this study. 4.2 Sample and Data Collection Data were collected via an online survey of a total of 127 strategic alliances (90 domestic and 37 foreign) with 304 respondents. All of the respondents were individuals in charge of the strategic alliances list in a public institu- tion that had active alliance activities and agreements (at least one joint strategic alliance activity). We followed up the online survey with email reminders to the respondents. From the total population of 127 strategic alliances, we received responses from 86, although 8 of these alliances were categorised as outliers (more than 10% incomplete data). As such, 78 strategic alliances were counted for this research, giving an effective response rate of 67%. Table 2 contains the respondent profile. The majority of the re- spondents were from organisations that had been estab- lished for more than 20 years, public institutions, which had already collaborated with an alliance institution more than three years ago, and had a term agreement of longer than five years. 44 Organizacija, V olume 57 Issue 1, February 2024 Research Papers No Constructs Dimensions 1. Strategic Alliance Performance (SAP) 2. Dynamic Learning Capability (DLC) 3. Relationship Capital (RC) Trust (T) Commitment (I) 4. Surfacing (S) Information Acquisition (SIA) Information Encoding (SIE) Information Sharing (SIS) Information Internalisation (SII) 5. Joint Learning Structure (JLS) Strategic Alignment (JLSSA) Teamwork for Problem Solving (JLSTS) Goals Management Systems (JLSGS) 6. Knowledge Acquisition (KA) Direct Exchange Acquisition (KAD) Alliances (KAA). Table 1: Research Constructs and Dimensions 5 Analyses and Results The data were analysed using measurement model and structural model analysis. The steps are elaborated in detail below. 5.1 Measurement Model Analysis The first step in assessing measurement model validity is to examine the size and significance of the loadings, reli- ability, and convergent and discriminant validity. All of the latent variables or constructs met the existing reliability and validity threshold. All latent variables showed reliabil- ity as indicated by a Cronbach’s alpha value ≥ 0.50. This value represents “satisfactory to good” when interpreting internal consistency reliability since this study involves social science research (Hair, Black, Babin, & Anderson, 2019). All of the constructs were valid and reliable as all of the Cronbach’s alpha, reliability, and Average Vari- ance Extracted (A VE) values were above their respective thresholds (Cronbach’s alpha: ≥ 0.50; Reliability: ≥ 0.70; A VE ≥ 0.50). As such, each construct explained more than 50% of the variance of its indicators. Only one dimension under the knowledge acquisition construct had a validity value below the threshold, namely direct exchange acqui- sition (Cronbach’s alpha: 0.597; A VE: 0.420), although its reliability value (0.750) above the threshold (≥ 0.5) meant it could still be included. After calculating the PLS algorithm from the initial 59 indicators, the outer loading results showed that most indicators were above the threshold (≥ 0.708; Hair et al., 2019), except for four: SAP5 (0.073), DLC6 (0.064), JLS- SA9 (-0.023), and KAD4 (0.039). Those four indicators were far below the threshold as a result of the reverse ques- tions. Some of the respondents were unaware of these and submitted answers mistakenly. Reliable and valid results were subsequently obtained after deleting those four indi- cators and recalculating the PLS algorithm for the remain- ing 55 indicators. All of the latent variables or constructs thus met the reliability and validity threshold. Meanwhile, all variables showed reliability based on their threshold Cronbach’s alpha value ≥ 0.7 while all outer loading val- ues were already above the threshold ≥ 0.5 (Hair et al., 2019). The next step was to assess the discriminant validity to determine how uniquely the indicators of a construct represented that construct versus the extent to which it was correlated with all other constructs in the model (Hair et al., 2019). The A VEs of two constructs were compared di- rectly to the shared variance between the two constructs, 45 Organizacija, V olume 57 Issue 1, February 2024 Research Papers Table 2: Respondent Profile Profile Number Percentage 1. Establishment > 20 years 63 80.77 6–20 years 13 16.67 < 5 years 0 0 Not Available 2 2.56 2. Type of Ownership Public Institution 42 53,85 Private Organisation 26 33.33 Other 8 10.26 Not Available 2 2.56 3. Collaboration Timeframe From year to now (2021–2022) 19 24.36 3 years ago (2018–2020) 14 17.95 > 3 years ago (before 2018) 43 55.13 Not Available 2 2.56 4. Term of Agreement Period > 5 years 38 48.72 2–5 years 25 32.05 < 2 years 13 16.67 Not Available 2 2.56 Total 78 with a guidance threshold value >0.7 (Hair et al., 2019). Based on the Fornell–Larcker criterion, five indicators were deleted to meet the requirements – JLST1, JLST2, JLST3, JLSSA2 and KAD1 – to give a total of nine deleted indicators. After deleting those five indicators, each con- struct had a value above the other constructs. For exam- ple, strategic alliance performance had the highest value (Fornell–Larcker: 0.851) for its correlation with strategic alliance performance compared to the correlation value with other constructs. Based on the cross-loadings in the discriminant validity assessment, each indicator in the construct represents the highest value compared to the cor- relation value with other constructs. For example, strategic alliance performance (cross-loading) had the highest value on indicators SAP1 (0.875), SAP2 (0.891), SAP3 (0.793), SAP4 (0.924), and SAP6 (0.760) for its correlation with strategic alliance performance compared to the correlation values with other constructs (dynamic learning capabili- ty, relationship capital, surfacing, joint learning structure, and knowledge acquisition). The heterotrait–monotrait ra- tio (HTMT) criterion in discriminant validity assessment is defined as the mean value of the indicator correlations across constructs relative to the mean of the average corre- lations of indicators measuring the same construct (Hair et al., 2019). Henseler et al., in Hair, Black, Babin, and An- derson (2019), recommended a value of ≤ 0.90. After us- ing the bootstrapping procedure with a basic setting of 500 subsamples, most of the indicators were found to be below the HTMT ratio threshold (≤ 0.9), except for knowledge acquisition (0.907). However, the knowledge acquisition indicators were already below the threshold (0.767) in the previous Fornell–Larcker discriminant validity assess- ment; as such, all of the latent constructs explained more of the variance in their item measures than they shared with another construct. 46 Organizacija, V olume 57 Issue 1, February 2024 Research Papers Table 3: Discriminant Validity: Heterotrait–Monotrait Ratio (HTMT) No Variables Strategic Alliance Performance Dynamic Learning Capability Relationship Capital Surfacing Joint Learning Structure Knowledge Acquisition 1. Strategic Alliance Performance 1 2. Dynamic Learning Capability 0.808 3. Relationship Capital 0.726 0.783 4. Surfacing 0.867 0.876 0.766 5. Joint Learning Structure 0.809 0.809 0.609 0.838 Table 4: Structural Model Analysis Assessment Threshold Value 1. Collinearity – Vari- ance Inflation Factor (VIF) A value above 3 is likely to indicate a problem; high collinearity is defined as a value above 5. Most of the indicators < 3, except for Sur- facing (3.339) and Knowledge Acquisition (3.047); however, these were still accept- able as the values were far below 5 (Hair et al., 2019). 2. Size and significance of the structural path relationship–p – assess (R²) The R² value is between 0 and 1. Since 0 indicates no relationship and 1 is a perfect re- lationship, the higher the value the greater the explanatory power of the structural model. R² values of 0.75, 0.50, and 0.25 can be considered substantial, moderate, and weak, respectively. All of the R² values were above the thresh- old (>0.05). All of the endogenous constructs had a moderate value of between 0.50 and 0.75. R² of Strategic Alliance Performance: 0.571 (57.1%); Dynamic Learning Capability: 0.768 (76.8%). 3. The effect size – (f²) Effect size is assessed to determine whether the removal of a predictor construct from the structural model has a substantive impact on the endogenous construct. Based on guidelines from Cohen (Hair et al., 2019), f² values of 0.02, 0.15, and 0.35, respectively, represent small, medium, and large effects of an exogenous construct, while an effect size < 0.02 indicates no effect. All the endogenous constructs had small and medium effects based on the thresh- old (≥ 0.02). (f²) values: Dynamic Learning Capability (1.360), Relationship Capital (0.061), Surfacing (0.075), Joint Learning Structure (0.099), Knowledge Acquisition (0.134). 4. Predictive relevance based on Q² A value > 0 indicates that the predictive accu- racy of the path model is acceptable for that construct. All of the endogenous constructs had a Q² value > 0, thus indicating that the path model’s predictive accuracy was accept- able. The Q² value assessment for all endogenous constructs is above 0: Strategic Alliance Performance (0.366), Dynamic Learning Capability (0.499). 47 Organizacija, V olume 57 Issue 1, February 2024 Research Papers 5.2 Structural Model Analysis We performed structural model analysis using Smart- PLS. Based on Hair et al. (2019), there are five steps in assessing a structural model: assessing collinearity, eval- uating the size and significance of the structural path re- lationship, assessing R², assessing the f² effect size, and evaluating the predictive relevance based on Q². We first assessed collinearity, which involved comput- ing the Variance Inflation Factor (VIF) for each indicator. All of the inner VIF values were below the threshold of 3 except for surfacing and knowledge acquisition, although this was still acceptable since the value was far below 5 (Hair et al., 2019). The second step was to conduct boot- strapping to evaluate the size and significance of the struc- tural path relationship. The result showed that all the R² values were above the threshold (>0.05). The third step was to assess R²; here, the result showed that all the en- dogenous constructs had a moderate value of between 0.50 and 0.75. The fourth step was to assess the f² effect size, which involved determining whether the removal of a pre- dictor construct from the structural model had a substan- tive impact on the endogenous construct. All of the endog- enous constructs had small and medium effects. The fifth step involved assessing the predictive relevance based on Q². The blindfolding procedure was conducted to obtain the Q² value. All of the endogenous constructs had a Q² value greater than zero, which indicates that the path mod- el’s predictive accuracy is acceptable. The Q² value assess- ment for all endogenous constructs is above zero. Table 4 contains a detailed breakdown of the results. A path coefficient value of +1 indicates a perfect pos- itive relationship, 0 indicates no relationship, and a val- ue of -1 indicates a perfect negative relationship (Hair et al., 2019). All of the path coefficient values were positive since they were between -1 and 1. All of the correlations were significant, as indicated by the T statistic ≥ 1.96 (Hair et al., 2019). All of the correlations were connected since the P-values were below the threshold of ≤ 0.05 (Hair et al., 2019). Figure 2: Path Diagram 48 Organizacija, V olume 57 Issue 1, February 2024 Research Papers The results for all hypotheses in the research model are summarised in Table 5 below: No Hypothesis t-Value P-Value Remark Summary H1 Relationship Capital is positively related to dynamic learning capability. 2.236 0.026 Positive Significant H1 Accepted H2 Surfacing is positively related to dynamic learning capability. 2.058 0.040 Positive Significant H2 Accepted H3 Joint Learning Structure is positively related to dynamic learning capability. 2.484 0.013 Positive Significant H3 Accepted H4 Knowledge Acquisition is positively related to dynamic learning capability. 3.260 0.001 Positive Significant H4 Accepted H5 Dynamic Learning Capability is positively relat- ed to strategic alliance performance. 12.469 0.000 Positive Significant H5 Accepted Table 5: Hypotheses Result 6 Conclusion, Implication, and Future Studies Several conclusions can be drawn from the above find- ings. First, all of the hypotheses examined in this research are accepted. This signifies that all constructs from a com- plete learning framework affect dynamic learning capabil- ity, while dynamic learning capability also affects strategic alliance performance. Knowledge acquisition (t-value: 3.260; p-value: 0.001) has the greatest impact on creating dynamic learning ca- pability. The strongest effect derives from the construct of alliances with the question: KAA_3 In alliance with the alliance institution, we develop alliances and cooperation with participants in the development of joint research projects. This supports previous research by Ortiz et al. (2018) on how external knowledge acquisition formed by two dimensions, direct market exchange and cooperation agreement or strategic alliances, can affect strategic alli- ance performance through dynamic learning capability. It indicates that the public institution and its alliances already conduct routine activities within a joint research project, as shown by how these activities provided the most support to the success of the strategic alliance performance. Meanwhile, surfacing, notably from information in- ternalisation, has the lowest impact on the creation of dy- namic learning capability that leads to strategic alliance performance, with the question: SII_3 In alliance with the alliance institution, employees participating in the alliance are entitled to use all the alliance information of our or- ganisation. This finding implies a process of information internalisation, which refers to the organisation’s process of expediting the alliance’s proprietary technology under its ownership to become individual information (Yue et al., 2018). As such, there is scope for improvement within the information internalisation activities. This can be con- ducted by alliance institutions through socialisation on the availability of the alliance information result given the po- tential for a lack of awareness concerning its availability. In the area of relationship capital, other improvement activities for the alliance institution and its wider strate- 49 Organizacija, V olume 57 Issue 1, February 2024 Research Papers gic alliances centre on the lowest impact on creating a dy- namic capability that led to strategic alliance performance, with the question RCC_4 We will definitely continue the relationships with the alliance institution. This emphasises the process of learning between alliances that can influ- ence alliance performance through trust and relationship commitment (Shan et al., 2018). Improvement can involve a process of review and discussion among the alliance in- stitutions to update the objective of forming strategic alli- ances and the aspects requiring improvement within both parties for the strategic alliances to continue. Improvement in the area of joint learning structure is based on the lowest impact in creating a dynamic capa- bility that led to strategic alliance performance with the question JLSSA_8 In alliance with the alliance institution, we emphasise the importance of good organisational in- ter-functional relationships. This finding implies strategic alignment in which products and processes are improved and where the company’s competencies, technology, and innovation are exploited and synergised while continuous- ly stimulating the new knowledge available to functions in addition to cross-learning by enhancing the company’s ability (Galeazzo et al., 2016). Alliance institutions can conduct this type of improvement by emphasising the im- portance of good organisational inter-functional relation- ships and through socialisation to build awareness in this area. Improvement in dynamic capability can increase the performance of the collaboration and engender improve- ment in dynamic learning capability, as based on the low- est impact in creating strategic alliance performance with the question DLC_1 In alliance with the alliance institu- tion, we have routines to identify, value, and import new information and knowledge. This finding implies a posi- tive effect of dynamic learning capability on the compa- ny’s ability to create value (Rashidirad & Salimian, 2020). The improvement can be effected by the alliance institu- tions through routine gatherings, workshops, or group fo- rum discussions to identify, value, and import new infor- mation and knowledge. This research has certain limitations. First, it relies on limited data due to the availability of the respondents since they could only be reached by email. The limited volume of data can also be attributed to how only specific individ- uals, that is, those in charge, were eligible to respond. The restriction regulation from the international respondents served as a further constraint during the data collection process. Second, the types of strategic alliances estab- lished by the alliance institution were specific to the learn- ing area in only certain topics related to the government, institution, or private organisation. Future research may be warranted in organisations other than public institutions that have different character- istics and also to consider whether the constructs in a com- plete learning framework impact the creation of dynamic learning capability in supporting the objective of strate- gic alliance performance. Furthermore, the scope of stra- tegic alliance collaboration can be expanded beyond the learning area to include, for example, the manufacturing industry, export-oriented products, or digital services that require knowledge related to technology development. Future research may also comprise longitudinal studies to identify the data result trend, including the impact of the learning framework in areas other than dynamic learning capability, for example, dynamic integration and dynamic reconfiguration capability (Abbas, Raza, Nurunnabi, Mi- nai, & Bano, 2019), to obtain a complete understanding. Acknowledgement This work was supported by the University of Indonesia under project No: NKB-063/UN2.RST/HKP.05.00/2022 “Hibah Publikasi Terindeks International (PUTI) Pascasar- jana Tahun Anggaran 2022-2023”. We are also immensely grateful to Ibu Doctor Arlyana Abubakar dan Bapak Janu Dewandaru, M.A., from BI Institute. Literature Abbas, J., Raza, S., Nurunnabi, M., Minai, M. S., & Bano, S. (2019). The impact of entrepreneurial business net- works on firms’ performance through a mediating role of dynamic capabilities. Sustainability, 11(11). http:// doi.org/10.3390/su11113006 Ahmad, S., Omar R., & Quoquab F. (2019). Corpo- rate sustainable longevity: Scale development and validation. SAGE Open, 9(1). http://dx.doi. org/10.1177/2158244018822379 Arief, A., Wahab, I. H., & Muhammad, M. (2021). Barriers and challenges of e-government services: A systematic literature review and meta-analyses. IOP Conference Series. Materials Science and Engineering, 1125(1). http://dx.doi.org/10.1088/1757-899X/1125/1/012027 Arvanitis, S., Lokshin, B., Mohnen, P., & Woerter, M. (2015). Impact of external knowledge acquisition strategies on innovation: A comparative study based on Dutch and Swiss panel data. Review of Indus- trial Organization, 46(4), 359–382. https://dx.doi. org/10.2139/ssrn.2206201 Borchardt, M., Pereira, G., Milan, G., Scavarda, A., Nogueira, E., & Poltosi, L. (2022). Industry 5.0 be- yond technology: An analysis through the lens of business and operations management literature. Orga- nizacija, 55(4), 305–321. https://doi.org/10.2478/orga- 2022-0020 Chen, Y-C., & Hsieh, T-C. (2014). Big data for digital government: Opportunities, challenges, and strat- egies. International Journal of Public Administra- tion in the Digital Age, 1(1), 1–14. doi:10.4018/ijpa- da.2014010101 50 Organizacija, V olume 57 Issue 1, February 2024 Research Papers Chrisanty, F. N., Gunawan, M. S., Wijayanti, R. W., & Soetjipto, B. W. (2021). The role of transformation- al entrepreneurship, readiness to change and coun- terproductive work behavior in enhancing employee performance. Organizacija, 54(1), 63–81. http://doi. org/10.2478/orga-2021-0005 Cousin, P. D., Handfield, R. B., Lawson, B., & Petersen, K. J. (2006). Creating supply chain relation capital: The impact of formal and informal socialization process- es. Journal of Operations Management, 24, 851–863. https://doi.org/10.1016/j.jom.2005.08.007 Davenport, T. H., & Prusak, L. (1998). Working knowl- edge. How organizations manage what they know. Boston, MA: Harvard Business School Press. Dhaundiyal, M., & Coughlan, J. (2020). The impact of alliance justice capability on the performance of stra- tegic alliances in the Indian IT sector: The mediating role of inter-firm commitment. Cogent Business & Management, 7(1), 1719587. https://doi.org/10.1080/ 23311975.2020.1719587 Fey, C., & Birkinshaw, J. (2005). External sources of knowledge, governance mode, and R&D performance. Journal of Management, 31(4), 597–621. https://doi. org/10.1177/0149206304272346 Frederico, G. F. (2021). From Supply Chain 4.0 to Supply Chain 5.0: Findings from a systematic literature review and research directions. Logistics, 5(3), 49. https://doi. org/10.3390/logistics5030049 Furnival, J., Boaden, R., & Walshe, K. (2019). A dynamic capabilities view of improvement capability. Journal of Health Organization and Management, 33(7/8), 821–823. http://doi.org/10.1108/JHOM-11-2018-0342 Galeazzo, A., Furlan, A., & Vinelli, A. (2016). The organi- zational infrastructure of continuous improvement – an empirical analysis. Operations Management Research, 10, 33–46. http://dpoi.org/10.1007/s12063-016-0112-1 Glaister, K. W., & Buckley, P. J. (1998). Measures of performance in UK international alliances. Or- ganization Studies, 19(1), 89–118. http://doi. org/10.1177/017084069801900105 González-Pérez, L. I., and Ramírez-Montoya, M. S. (2022). Components of education 4.0 in 21st century skills frameworks: Systematic review. Sustainabili- ty, 14(3), 1493. http://doi.org/10.3390/su14031493 Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th Ed.). Pearson Prentice Hall. Haapanen. L., Hurmelinna-Laukkanen, P., Puumalainen, K. (2020). When Strategic consensus matters: dynamic managerial capabilities and firm internalization as seen by TMT. Cross Cultural & Strategic Management. 27(3), 285-315 Emerald Publishing Limited. http://doi. org10.1108/CCSM-09-2018-0134 Hijal-Moghrabi, I., Sabharwal, M., & Ramanathan, K. (2020). Innovation in public organizations: Do gov- ernment reforms matter? The International Journal of Public Sector Management, 33(6), 731–749. http:// dx.doi.org/10.1108/IJPSM-04-2020-0106 Lavie, D. (2006). Capability reconfiguration: An analysis of incumbent responses to technological change. Acad- emy of Management Review, 31(1), 153–174. https:// doi.org/10.5465/amr.2006.19379629 Lenart-Gansiniec R. (2016). Relational capital and open innovation in search of interdependency. Procedia - Social and Behavioral Sciences, 220, 236–242. https:// doi.org/10.1016/j.sbspro.2016.05.495 Lin, Y ., & Wu, L-Y . (2014). Exploring the role of dy- namic capabilities in firm performance under the re- source-based view framework. Journal of Business Research, 67(3), 407–413. https://doi.org/10.1016/j. jbusres.2012.12.019 Matysiak, L., Rugman, A. M., & Bausch, A. (2018). Dy- namic capabilities of multinational enterprises: The dominant logics behind sensing, seizing, and trans- forming matter! Management International Review, 58(2), 225–250. https://doi.org/10.1007/s11575-017- 0337-8 McKinsey (2023). The State of Organizations. Available at: https://www.mckinsey.com/featured-insights/mck- insey-live/webinars/the-state-of-organizations Morrison, M., & Mezentseff, L. (1997). Learning alli- ances – a new dimension of strategic alliances. Man- agement Decision, 35(5), 351–357. http://dx.doi. org/10.1108/00251749710173715 Nguyen, P. T. M, Mai, K. N, & Nguyen, P. N. D. (2021). Alliance management practices for higher trust, com- mitment and inter-organizational relationship perfor- mance: Evidence from travel companies in Vietnam. Sustainability, 13, 9102. https://doi.org/10.3390/ su13169102 Ortiz, B., Donate, M. J., & Guadamillas, F. (2018). In- ter-organizational social capital as an antecedent of a firm’s knowledge identification capability and external knowledge acquisition. Journal of Knowledge Man- agement, 22(6), 1332–1357. http://doi.org/10.1108/ JKM-04-2017-0131 Osterberg, R. (1993). A new kind of company with a new kind of thinking. In M. Ray and A. Rinzler (Eds), The new paradigm in business. New York: Putnam. Pereira, A. C., & Romero, F. (2017). A review of the mean- ing and the implications of the Industry 4.0 concept. Procedia Manufacturing, 13, 1206–1214. https://doi. org/10.1016/j.promfg.2017.09.032 Popa, I., Dobrin, C., Popescu, D., & Draghici, M. (2011). Competitive advantage in the public sector. Theoreti- cal and Empirical Researches in Urban Management, 6(4), 60–66. Rashidirad, M., & Salimian, H. (2020). SMEs’ dynamic capabilities and value creation: The mediating role of competitive strategy. European Business Review, 51 Organizacija, V olume 57 Issue 1, February 2024 Research Papers 32(4), 591–613. http://doi.org/10.1108/EBR-06-2019- 0113 Rupčić, N. (2020). Guest editorial. The Learning Orga- nization, 27(4), 277–289. http://dx.doi.org/10.1108/ TLO-05-2020-254 Savino, T., Messeni Petruzzelli, A., & Albino, V . (2017). Search and recombination process to innovate: A re- view of the empirical evidence and a research agenda. International Journal of Management Reviews, 19(1), 54–75. https://doi.org/10.1111/ijmr.12081 Schuh, G., Anderl, R., Dumitrescu, R., Kruger, A., & ten Hompel, M. (2020). Industrie 4.0 Maturity Index. Man- aging the digital transformation of companies. Update 2020. Acatech – National Academy of Science and En- gineering. Available at: https://en.acatech.de/publica- tion/industrie-4-0-maturity-index-update-2020/ Senge, P. (1992). The fifth discipline: The art and prac- tice of the learning organization. Canberra: Random House. Shan, L., Dan, L., & Qiu, Y . (2018). Study of the impact mechanism of inter-organizational learning on alliance performance–with relationship capital as the mediator. Neural Computing and Applications, 32, 117–126. https://doi.org/10.1007/s00521-018-3783-8 Sindhwani, R., Afridi, S., Kumar, A., Banaitis, A., Luthra, S., & Singh, P. L. (2022). Can Industry 5.0 revolution- ize the wave of resilience and social value creation? A multi-criteria framework to analyze enablers. Technol- ogy in Society, 68, 101887. https://doi.org/10.1016/j. techsoc.2022.101887 Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Man- agement Journal, 18(7), 509–533. Available at: www. jstor.org/stable/3088148 Yue, Q., Hua, X., & Quan, M. (2018). Structural equation model analysis of information systems in cooperative organizations: Focusing the role of cooperative expe- rience and information process mechanism, Inf Syst E-Bus Manage , 18, 603–615. https://doi.org/10.1007/ s10257-018-0387-x Yoshino, M., & Rangan, S. (1995). Strategic alliances: An entrepreneurial approach to globalization. Boston: Harvard Business School Press. Zhou, K. Z., & Wu, F. (2010). Technological capability, strategic flexibility, and product innovation. Strate- gic Management Journal, 31(5), 547–561. http://doi. org/10.1002/SMJ.830 Febri Nila Chrisanty is a doctoral student at the University of Indonesia, Faculty of Economics and Business, Depok, Indonesia. She is a lecturer at the Institute of Technology and Business Jakarta. She completed her magister’s degree in International Management at Magister Management, University of Indonesia, Indonesia. She has 20 years of practical experience in the financial industry. ORCID: https:// orcid.org/0000-0002-6316-4550 Riani Rachmawati is a lecturer and researcher at the Faculty of Economics and Business, Universitas Indonesia. She completed her Doctor of Philosophy (PhD) in Labour and Industrial Relations at the University of Birmingham and her Master’s degree in Industrial Relations and Human Resources Management at the University of Warwick. riani.rachmawati@ui.ac.id. Prijono Tjiptoherijanto is a researcher and Professor at the University of Indonesia, Faculty of Economics and Business, Depok, Indonesia. He completed his doctoral degree at the University of Hawaii in 1981 and his Master’s degree at the University of the Philippines in 1977. 52 Organizacija, V olume 57 Issue 1, February 2024 Research Papers Appendix: List of Questionnaires No Code Questionnaires SLF 1. Relationship Capital 1.1 Trust RCT_1 RCT_2 RCT_3 RCT_4 We trust that the alliance institution’s decisions are beneficial for both parties. We trust the alliance institution’s professional competence and abilities. We trust the alliance institution’s ability to implement the objectives. We highly trust the alliance institution through the formal contracts. 0.912 0.899 0.897 0.908 1.2 Commitments RCC_1 RCC_2 RCC_3 RCC_4 We have a strong sense of loyalty to the relationships with the alliance institution. We dedicate enough resources to maintain the relationships with the alliance institution. We always try to improve the management of the relationships with the alliance institution. We will definitely continue the relationships with the alliance institution. 0.900 0.938 0.901 0.891 2. Surfacing 2.1 Information Acquisition SIA_1 SIA_2 SIA_3 In alliance with the alliance institution, we archived all the history and information of the alliance. In alliance with the alliance institution, we record all important results and problems in the alliance in text or other forms (e.g. manually recorded, dashboard system). In alliance with the alliance institution, we regularly report major events to the organisation management team. 0.897 0.880 0.837 2.2 Information Encoding SIE_1 SIE_2 SIE_3 In alliance with the alliance institution, we form and gradually improve our organisation’s method of managing the alliance. In alliance with the alliance institution, we have an alliance manual and other documents to guide decision-making during the alliance period. In alliance with the alliance institution, we summarised the experience of the alliance that spreads to all other alliances 0.917 0.896 0.903 2.3 Information Sharing SIS_1 SIS_2 SIS_3 In alliance with the alliance institution, we regularly exchange alliance information and ex- periences (e.g. webinars, policy news, workshops) with other colleagues of our organisation. In alliance with the alliance institution, we often exchange information and experience from the alliance (such as through webinars, policy news, and workshops) with the managerial staff of our organisation’s other alliances via an informal process. In alliance with the alliance institution, our organisation encourages us to share alliance management experience (such as through webinars, policy news, and workshops) with other managerial staff in our organisation. 0.914 0.910 0.886 53 Organizacija, V olume 57 Issue 1, February 2024 Research Papers No Code Questionnaires SLF 2.4 Information Internalisation SII_1 SII_2 SII_3 In alliance with the alliance institution, we provide information on training and research pro- grammes for employees participating in the alliance. In alliance with the alliance institution, we provide external training for employees partici- pating in the alliance. In alliance with the alliance institution, employees participating in the alliance are entitled to use all the alliance information of our organisation. 0.907 0.883 0.789 3. Joint Learning Structure 3.1 Strategic Alignment JLSSA_1 JLSSA_2 JLSSA_3 JLSSA_4 JLSSA_5 JLSSA_6 JLSSA_7 JLSSA_8 JLSSA_9 In alliance with the alliance institution, in our organisation, the goals, objectives, and strate- gies of the alliance are communicated to us. In alliance with the alliance institution, potential alliance objectives are screened for consis- tency with our business strategy. In alliance with the alliance institution, at our organisation, the alliance process is kept in step with our business strategy. In alliance with the alliance institution, we believe that focusing on the long-term alliance will lead to better overall performance than focusing exclusively on short-term goals. In alliance with the alliance institution, we routinely review and update a long-range strategic plan for alignment with the alliance. In alliance with the alliance institution, our organisation’s functions work interactively. In alliance with the alliance institution, the functions in our organisation cooperate to resolve conflicts between them when they arise. In alliance with the alliance institution, we emphasise the importance of good organisational inter-functional relationships. In alliance with the alliance institution, we are not encouraged to communicate well with different functions in the organisation. (Reverse Question) 0.816 NA 0.842 0.776 0.845 0.893 0.824 0.770 NA 3.2 Teamwork for Problem Solving JLSTS_1 JLSTS_2 JLSTS_3 JLSTS_4 JLSTS_5 JLSTS_6 In alliance with the alliance institution, we encourage employees to work together to achieve alliance common goals, rather than encourage competition among individuals. In alliance with the alliance institution, we form teams to solve alliance problems. In alliance with the alliance institution, employee teams are encouraged to try and solve alliance problems independently as much as possible. In alliance with the alliance institution, we are encouraged to make suggestions related to the alliance on improving performance at this organisation. In alliance with the alliance institution, we encourage employees to exchange opinions and ideas related to the alliance. In alliance with the alliance institution, we encourage employees to work as a team related to this alliance. NA NA NA 0.803 0.894 0.869 54 Organizacija, V olume 57 Issue 1, February 2024 Research Papers No Code Questionnaires SLF 3.3 Goals Management Systems JLSGS_1 JLSGS_2 JLSGS_3 JLSGS_4 In alliance with the alliance institution, our reward system truly recognises the people who contribute the most to our organisation related to the alliance. In alliance with the alliance institution, the incentive system at this organisation is fair at rewarding people who accomplish company objectives through the alliance. In alliance with the alliance institution, the incentive system at this organisation encourages us to reach the organisation’s goals through the alliance. In alliance with the alliance institution, our incentive system encourages us to pursue the organisation’s objectives vigorously through the alliance. 0.880 0.930 0.949 0.905 4. Knowledge Acquisition 4.1 Direct Exchange Acquisition KAD_1 KAD_2 KAD_3 KAD_4 KAD_5 In alliance with the alliance institution, we get the exquisites n the technological develop- ment organisation. In alliance with the alliance institution, we obtain knowledge of the alliance institution’s pro- fessional experience. In alliance with the alliance institution, we obtain knowledge from the external consultants or the alliance institution. In alliance with the alliance institution, we do not usually acquire technological licences. (Reverse Question) In alliance with the alliance institution, we acquire complex technology or knowledge and incorporate it into equipment, specialised machinery, or systems. NA 0.864 0.897 NA 0.551 4.2 Alliances KAA_1 KAA_2 KAA_3 In alliance with the alliance institution, we develop alliances and cooperation with other organisations. In alliance with the alliance institution, we develop alliances and cooperation with the organ- isation’s supply chain function. In alliance with the alliance institution, we develop alliances and cooperation with partici- pants in the development of joint research projects. 0.860 0.910 0.914 5. Dynamic Learning Capability DLC_1 DLC_2 DLC_3 DLC_4 DLC_5 DLC_6 In alliance with the alliance institution, we have routines to identify, value, and import new information and knowledge. In alliance with the alliance institution, we have routines to assimilate new information and knowledge. In alliance with the alliance institution, we have transformed existing information into new knowledge. In alliance with the alliance institution, we use knowledge in value creation effectively. In alliance with the alliance institution, we develop new knowledge effectively. In alliance with the alliance institution, we do not learn new things within the organisation. (Reverse Question) 0.833 0.842 0.852 0.877 0.863 NA 55 Organizacija, V olume 57 Issue 1, February 2024 Research Papers No Code Questionnaires SLF 6. Strategic Alliances Performance SAP_1 SAP_2 SAP_3 SAP_4 SAP_5 SAP_6 The objectives for which this partnership with the alliance institution was established are being met. We are satisfied with the strategic alliance performance of the alliance with the alliance institution. The alliance institution appears to be satisfied with the performance of the alliance. We are satisfied with the overall performance of the alliance with the alliance institution. The alliance institution does not appear satisfied with the overall performance of the alli- ance. (Reverse Question) Our organisation’s capabilities have been greatly enhanced due to the alliance with the alli- ance institution. 0.875 0.891 0.793 0.924 NA 0.760