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Competition is usually understood as a multistage game between two or several parties/companies seeking to achieve dominance/power over others. However, an increase in risk, uncertainty and ambiguity drives companies toward each other to cooperate and share best practices, capacities and resources, especially knowledge, and innovate and cocreate new value. For that purpose, effective interorganizational learning becomes invaluable. Interorganizational learning refers to several aspects: transfer of knowledge from one organization to the other or others, mutual knowledge exchange and/or creation of new knowledge as a consequence of mutual knowledge exchange and learning. By intensifying network interactions, learning synergies can be achieved that could otherwise not occur.
Interorganizational learning is, therefore, a process that has the potential to evolve over time, along with the buildup of collaborative activities but also trust and mutual respect. In other words, learning and knowledge implementation is always dependent on practitioners – people at the interface of the organization and its environment, whereas an “organization” could refer to a team, unit, firm, cluster, network and even ecosystem. In addition, interorganizational learning is a multilevel process. If learning is considered from an organizational perspective, it starts with individual and team learning, ending in organizational learning, especially double-loop organizational learning if new knowledge is successfully transferred into organizational routines and practices. However, emphasis on learning could further stimulate search for partners, especially those in clusters and networks, for further knowledge acquisition or interorganizational learning.
In that way, networks can be considered learning entities (Gibb et al., 2017) and special learning contexts in which both exploratory and exploitative learning and knowledge transfer could and should occur. The involved practitioners could share their experiences, provide information about every day practices, their successes and failures and regarding other more complex issues such as used and developed technology and market relations. The process could then be considered in reverse: interorganizational learning or knowledge exchange first stimulates individual and team learning, leading to further organizational learning if knowledge is successfully transferred into organizational routines and practices. This could provide an additional stimulus for further interorganizational learning.
However, practitioners should keep in mind that this process tends to be slower than the organizational or intraorganizational learning (Holmqvist, 2009) as it involves entities of various kinds with different strategic orientations, motives for collaboration and organizational culture. In general, an effective interorganizational learning could occur if and when a high level of trust is established. For that reason, managing interorganizational learning could be considered a special and distinct managerial capability. In addition, managers should make sure the newly gained knowledge is compatible to their organization not only regarding its content but also regarding its value foundation, to ensure effective transfer and implementation.
Practitioners should realize that interorganizational learning provides a continuum that has several aspects (Lane et al., 2006): knowledge gained externally could be recognized as valuable through exploratory learning; it could then be absorbed through transformative learning, meaning that an organization changes its routines; and that knowledge could be then used to create new knowledge/added value through exploitative learning. Interorganizational learning does not have to be only active. It could also be passive/active in that one organization serves as a “teacher” and the other as a “student.” Methods of knowledge transfer could range from storytelling, observation, coaching and mentoring to more formal information and knowledge transfer practices. However, when engaging in collaborative activities, both or all parties seek to gain in terms of knowledge and learning, so interactive learning is likely to occur, resulting in co-creation of both explicit and tacit knowledge. However, for interorganizational learning to produce tangible benefits, organizations have to work on their absorptive capacity including knowledge assimilation and exploitation (Cohen and Levinthal, 1990). In that way, the quality and effectiveness of interorganizational learning is dependent on their characteristics (size, industry, value systems and mental models of the people involved) and their complementarity that enables joint knowledge co-creation. Learning and knowledge absorption is therefore a dynamic capability that is highly dependent on – practitioners and their absorptive capacity!
However, interorganizational learning and knowledge exchange are also very context dependent. Position in the network and entity size could play an important role. For example, position of small- and medium-sized companies in the supply chain could not be very prominent, which could make interorganizational learning and knowledge sharing very challenging (Bouncken et al., 2015). In addition, not all parties share the same interest and motivation for interorganizational learning and knowledge sharing, contributing to its slower pace and intensity. That is why, when engaging in a network creation (such as strategic alliances) and subsequently in interorganizational learning, the focus is on strategic considerations (Anand et al., 2021).
It seems that networks provide significant benefits in terms of new knowledge as interorganizational learning processes mostly focus on knowledge exploration, which was found to be the case in entrepreneurial corporate ventures (Schildt et al., 2005). Having all that in mind, it should be noted that interorganizational learning has been predominantly studied in the context of supply chains (Rajala, 2018; Hernández-Espallardo et al., 2010; Manuj et al., 2013). These networks, therefore, thrive on the fact that they create knowledge relevant for their individual performance improvements but also for optimization of the network, or better yet, complex and ever-evolving ecosystem of entities participating in certain value co-creation.
Interorganizational learning could and should therefore be studied in various contexts. In this special issue, practitioners could gain valuable knowledge on how to establish interorganizational learning in service networks, tourism industry, in Web-based platforms for research and development, among entrepreneurial ventures, with startups, and in the process of mainstreaming. In that way, both researchers and practitioners could expand their horizons regarding different subjects, objects and contexts involved in interorganizational learning.
Interorganizational learning in service networks
Service networks are especially challenging for studying interorganizational learning and their change and development on the basis of such learning and knowledge. Service networks can be observed from the internal perspective, by considering the creators of value, and from the external perspective, by considering the customer perception. Bringing both perspectives together, service networks aim to provide complex service packages with unified characteristics to customers by integrating multiple stakeholders. In that, value creation process time is of essence because it involves a series of transactions and exchange processes that occur over a period of time. In addition, the value creation can continue and be further developed if and when customers are engaged in the process. Communication is therefore key not only between service providers but also between them and the customers. Practitioners should keep in mind that the lack of timely communication can cause a lack of contextual understanding and disrupt the flow.
To achieve the network flow, boundaries of different entities should be seamless, making ground for organizational and interorganizational development on the basis of organizational and interorganizational learning and learning from other external stakeholders, especially customers. In that way, service provision becomes a construct and a co-construct of knowledge gained by implementing market and learning orientation in organizational and interorganizational relations in terms of exploration and exploitation of knowledge. In that way, interorganizational learning becomes a mechanism that contributes to the reduction of uncertainty and ambiguity and asymmetry of information between market constituents.
Even though the environment is continuously gaining in complexity, interorganizational learning can help reduce uncertainty and ambiguity by promoting interorganizational dialogue, which results in a variety of meanings that could stimulate creative action. That is why Peronard (2021) identifies two interorganizational learning objects: learning to create market knowledge and learning to apply it. In that way, interorganizational learning can, in general, help provide answers to the questions what, how and why is to be learned, resulting in a constellation of services and their delivery to customers across different providers.
However, in order for service providers to gain maximum benefits of interorganizational learning, the involved parties should also learn about potentials of mutual collaboration and learning and about modalities regarding mutual problem-solving. That is why Peronard (2021) simply defines interorganizational learning strategy as the ability to perform tasks together efficiently and effectively. However, that process should not be regarded as transactional but as transformational in that it can help transform mental models underlying certain value provision and contribute to new value creation. Joint sense-making and storytelling can be of assistance when trying to reach joint interpretations that would indicate a future course of action, especially regarding satisfying customers’ latent needs. However, the key issue that providers aim to achieve when engaging in joint learning and action is a high degree of compatibility among services as perceived by customers, often accompanied by supplementary services.
As suggested by Perrow (1999), interactions can be linear, following a causal sequence of events when errors can be easily spotted and corrected on the basis of single-loop organizational learning, and complex, when interactions are unpredictable, causing poor understanding of the nature of events and time-lagged interventions, requiring systems approach to make timely and adequate interventions. In addition, linkages between agents (service providers) can be loose, when there are few and indirect relations so that individual actions are rarely determined by actions of others, or tight, when there is a high degree of interdependence between network entities.
In case when there are only a few providers in a service network and they are tightly coupled in a linear fashion, Peronard (2021) suggests that the members engage in active learning. In such a system, clear policies, procedures and rules are needed, followed by strict adherence, so that the linear system functions sequentially and results in a desired service system for customers. This process can be optimized by exercising single-loop organizational learning so that errors are corrected by referring to organizational knowledge. On the other hand, when the system is complex and also tightly coupled so that entities are strongly interdependent, close coordination is necessary for the complex system to function and produce a synergistic effect. Peronard (2021) suggests an interactive learning in this type of organization. Interactive learning implies continuous dialogue and knowledge exchange, both explicit and tacit. However, it should be noted that system members (practitioners) should have high conceptual skills and use systems thinking to make strategic decisions that could adjust functioning of the complex system.
A lot less complicated situation is when the system functions in a linear fashion and its constituents are loosely coupled. As interactions are scarce and relations are determined, interorganizational learning is less intense. In other words, according to Peronard (2021), learning can be passive. However, undisrupted information flow and action learning on the part of each entity is necessary so that the service components continue to be improved, especially if costumer demands increase and/or change.
Finally, service network can be complex but its entities could be loosely coupled. Such systems operate on the basis of low centralization, usually in a network-like fashion with local adjustments, which makes them flexible and adaptable and even self-designing. For that to occur, dialogue, as well as information and knowledge sharing, is important so that each entity can adapt and transform on the basis of action learning and experimentation and, as suggested by Peronard (2021), experiential learning. When members engage in experiential learning, the whole service network system could be transformed on the basis of double-loop interorganizational learning based on joint sense-making. However, due to the fact that the system is loosely coupled, this process could be challenging. That is why practitioners should first change their mental models of independence and separation in favor of cooperation and coordination based on dialogue and the design of a common vision.
Interorganizational learning in the tourism industry
In this issue, readers could also learn about interorganizational learning in tourism industry for which Buhagiar (2021) designed a multilevel typology. Tourism is a very complex industry in which entities often collaborate and form clusters, networks and ecosystems. Ecosystems are formed in tourist destinations and consist of different market actors that establish different relations, which requires their managers to implement systems approach to identify ecosystem dynamics, adjust and align its operations, introduce improvements and innovations and produce synergistic effects. Clusters and networks are smaller parts of an ecosystem. Clusters are formed of entities (companies and institutions) that operate in close proximity and are involved in delivering some tourist value. They benefit from faster problem-solving, coordination of improvements and more efficient transactions. Clusters can attract more diverse market actors and their relations could become more complex, paving the way for the emergence of a network. It is not unusual that networks in the tourism industry emerge due to the development of mutual goals as well as a response to a crisis (Gustafsson et al., 2014) or some government intervention (Pinto and Cruz, 2012). Network members could benefit from enhanced networking and information sharing, mutual learning, knowledge exchange and innovation, which strengthen individual and collective capabilities and competitiveness.
Tourism clusters and networks can operate within a larger system (suprasystem) called tourism or service ecosystems that comprise different loosely coupled entities that share information and resources, cocreate value and develop by self-adjustment (Reynoso, et al., 2018). Such collaborative frameworks enable knowledge exchange and interorganizational learning (Wilke et al., 2019) by joint experimenting and improvisation, learning from failures and joint action (Holmqvist, 2003). Ecosystems are particularly well-suited platforms for interorganizational learning because their members share similarities in their knowledge domains, which makes them turn to each other more easily.
However, learning is nuanced and could occur on various levels and in various circumstances, as shown by Buhagiar (2021): in clusters, networks and ecosystems. For instance, when a cluster is characterized by service heterogeneity and increased competitiveness, which indicates lower levels of trust, interorganizational learning is, naturally, limited and could occur, for instance, through benchmarking or imitation. Power imbalance is also likely, making intraorganizational learning asymmetric in nature in that a dominant corporation could benefit from its strategic position and gain traction from joint resources such as local tradition. However, when the cluster is more tightly knit although still competitive, cooperative relations are more likely, opening the door for interactive interorganizational learning in which knowledge sharing is possible, followed by some knowledge co-creation. For example, a resort could cooperate with local farmers to adjust production and selling conditions.
In decentralized tourism networks consisting of various entities, interorganizational learning could be multidirectional. Its members are likely to meet and socialize, discuss matters officially but also in informal setting and share their cognitive thought processes, opinions and tacit knowledge. For instance, members of the network could team up to rebrand a destination based on joint understanding and consensus for the benefit of everyone involved and design new market offerings in which everyone could participate or contribute, such as festive programs, social events, tours, seminars and conferences.
Networks could also be the result of intentional actions with coordinated efforts and clear goals, which could make them horizontal or vertical in nature. In that context, interorganizational learning is determined by the network’s size, the size of entities involved and the degree of power symmetry between the network members. In case one entity plays the role of a focal organization (focal node in the network), members contribute to the achievement of its goals through sharing of knowledge and joint sense-making, making the learning process interactive in nature. However, other members could have minimal or no interaction as they maintain their roles as competitors and therefore not much learning occurs between them. If their relationship is collaborative in nature, this process could also intensify their interactions and learning. An entity having the focal role could be some institution, for example, chamber of tourism, which could coordinate activities in times of crisis or some opportunity.
Ecosystems represent larger platforms that include clusters and networks, enabling various learning relations. The whole tourism industry in a smaller country could be organized as one ecosystem or a specific destination could be coordinated as an ecosystem in large countries. In both cases, they represent repositories of knowledge and expertise, which they further develop to strengthen their competitive position. As they are prone to self-regulation, they share mutual values and vision and base their interactions on coordination mechanisms that could be informal or formal, representing ecosystem logistics.
Interorganizational learning in Web-based platforms for research and development
Activities of research and development require a pool of talent, knowledge and resources and the ability to absorb risks and failures. That is why these activities often involve cooperation of many organizations that learn together to jointly create new knowledge and hence new value. Their learning is very interactive and includes joint creation of new knowledge and transfer of knowledge from one organization to the other or others (Larsson et al., 1998). In that process, some organizations can engage in explorative learning by which they look for new knowledge and experiment by promoting teamwork and empowerment so that employees test new ideas and simulate their application. Other organizations could be more oriented toward exploitative learning by which they exploit existing knowledge to promote increases in productivity and efficiency. However, organizations can engage in both – exploration and exploitation of learning and knowledge so they could be described as being ambidextrous (Gupta et al., 2006).
Due to the problems of size, such learning is heavily supported by information and communication technology (ICT) to enable knowledge exploration and exploitation. Organizations that use them enable the development of individual and organizational learning and digital mindset. ICT is used to enhance the absorptive capacity as the ability of an organization to identify, gather and implement new knowledge in its value-creation process. To bring benefits, employees should accept and implement new technology. Its acceptance and usage is dependent on several aspects (Reichenbach et al., 2021). Some of them are related to the technology itself, whereas others have to do with the environment in which it is implemented. Thus, technology is likely to be accepted if it promises certain results that can be expected with high probability combined with its perceived usability or effort expectancy. Practitioners should put special emphasis on these factors to signal a high level of usefulness of a certain technology to the employees. However, social pressures to implement a certain technology should also be taken into account, together with different supportive or facilitating conditions. Even though facilitative factors are important, any kind of pressure can produce a negative attitude.
In this issue, in their paper, Reichenbach et al. (2021) address the problem of stimulating employees to use Web-based interorganizational learning platforms in research and development. For that purpose, they emphasize the importance of hedonic motivation as a driver of new technology acceptance, which is related to the aspect of pleasure, especially regarding flow experience that can be the result of using such technology. They investigated the effect of this factor along with previously identified factors on attitude and behavioral intention to adopt a new technology. They found that all relationships were positive and significant except the direct effect of social influence and facilitating conditions on attitude and the indirect effect of facilitating conditions and social influence on behavioral intention.
When subgroups or organizations that are explorative, exploitative or ambidextrous are considered, the results differed. In explorative organizations (such as universities), employee attitude to adopt Web-based technology was strongly influenced by performance and effort expectancies of that technology, indicating that they expected significant benefits from using that technology in interorganizational learning. To further stimulate usage of such technologies, practitioners should ensure greater automation, customization and flexibility of the system. In addition, in these organizations, effort expectancy, social influence and attitude seem to further affect their behavioral intention to adopt them. That is why teamwork and empowerment should be stimulated to enable greater usage of these systems.
In exploitative organizations (such as companies and government agencies using knowledge), performance expectancy was the most important driver to adopt Web-based platforms for interorganizational learning. In interorganizational learning, these organizations absorb knowledge from explorative organizations and implement it to create value. Facilitative conditions were also found to be important to stimulate technology usage. As they use technology to absorb knowledge, it is important to have a simulative environment to motivate them to use it more frequently. Tutorials, seminars and training courses could be of much help in this regard.
In ambidextrous organizations, performance and effort expectancy were also found to have a positive effect on attitude to adopt Web-based technologies. These factors, together with hedonic motivation and attitude were found to have a positive effect on behavioral intention to adopt them. These users probably show greater enthusiasm in using such technologies to learn something new, which causes them joy and results in the feeling of flow. Virtual experience fostered by artificial intelligence and flexibility can further stimulate the usage of these technologies.
Interorganizational learning by entrepreneurial ventures
Organizational learning research is usually focused on larger organizations. That is why startups and entrepreneurial ventures are a special field of research. These organizations are especially interesting because they do not yet have established processes, but they change and develop fast on the basis of continuous learning from various sources, while being constrained by a lack of resources. In essence, entrepreneurship is a process developed by learning or in short – entrepreneurship is learning (Cope, 2005).
Entrepreneurial ventures are often hit by events causing crisis. That is why it is interesting to discover how they handle crisis situations and how learning is of assistance. COVID-19 lockdown and restrictions have significantly affected entrepreneurial ventures and unfortunately represent a research topic par excellence when it comes to crisis management. These unfortunate events have caught many companies off guard and without enough resources, skills and knowledge to cope. However, even in these times, learning, especially interorganizational learning, could be a valuable survival mechanism. In such severe crisis situations, more than ever, entrepreneurial ventures could be dependent upon learning about customers, suppliers or employees to bridge the situation and survive.
In his paper, Haneberg (2021) looked into how knowledge-based entrepreneurial ventures fared during COVID-19 lockdown and how it affected their interorganizational learning. His initial hypothesis was that this high crisis situation would stimulate interorganizational learning to help them overcome adversities. In crisis situations, entrepreneurial ventures could be more prone to reach out to other organizations and look for solutions together. Entrepreneurial ventures often rely on social interactions with other entrepreneurs (Nogueira, 2019) making their social context especially important for learning and mutual support. Business incubators seem to be especially supportive with regard to learning (Fang et al., 2010), both with internal and external stakeholders. They have previously been found to be very helpful in times of uncertainty and increased dynamics (Wu et al., 2020). Knowledge-intensive industries have already been found to benefit from interorganizational learning through interpersonal relations (Pina-Stranger and Lazega, 2011).
Haneberg (2021) looked into lockdown effects on interorganizational learning in mid-May 2020 in Norway after the country went into lockdown on March 13. Practitioners could benefit from the questions he asked to measure entrepreneurial venture adversity. He asked whether lockdown affected their development of products and services, marketing and sales to existing customers, marketing and sales to new customers, financial situation and development of the organization. Results regarding marketing and sales showed strong correlation, so they were merged. Practitioners could also estimate their own degree of active responses reflecting intra and interorganizational activities by the questions that were used by Haneberg (2021) such as if the firm was doing/planning responses based on prior experiences, experiences of other firms’ responses, in collaboration with other firms and if the firm supported other firms in their responses.
The results showed that firms could be grouped into four categories: those that were neither negatively nor positively affected by the lockdown and showed a slightly lower than average degree of active responses in terms of collaboration with other firms or supporting other firms. The second group was affected in the same fashion but still did show a high degree of active responses collaborating with others. The third group was firms severely negatively affected with a low level of active responses. The forth group encompassed those significantly negatively affected but showing a high degree of active responses.
Practitioners could also use the questions by Haneberg (2021) to assess their level of interorganizational learning. For instance, practitioners could check if their firm has acquired new or important knowledge about products, services, customers, markets, strategies or financing from other firms; if other firms have contributed by building their knowledge and capabilities to better handle the situation; and if they consider the knowledge from other companies or created in collaboration with other companies as more important than their experiences.
It should be emphasized that, contrary to expectations, Haneberg (2021) found that lockdown actually diminished the level of intraorganizational learning among entrepreneurial ventures. There could be several explanations for this finding. One logical explanation could be that the firms were hit so severely that they simply lacked resources, ability and/or willingness to engage in intraorganizational learning. The reason could also lie in the fact that firm representatives did not feel comfortable solely using IT to communicate because of restrictions in real social interactions. In addition, it may have been too soon to conduct this type of research only two months into the lockdown as most activities were in the standstill mode. It is quite possible that entrepreneurs turned to themselves and their families knowing that there was no solution to the closed market, whereas some others did not have any problems and quickly directed their value creation and sales online so that they did not need any external help. It needs to be mentioned that some companies, probably those that were already predominantly online, actually benefited from the situation, again reducing their need to rely on others. This assumption is in line with another finding by Haneberg (2021) that the importance of social network for intraorganizational learning was not supported. Lockdown, such as this one, has never happened in history, so the circumstances could have frozen the entrepreneurs in their position and made them turn to themselves in either enjoying the unexpected benefits or facing challenges.
Learning with startups
One interesting avenue of research and practice is interorganizational learning with startups. Even though startups are known to collaborate and exchange ideas and knowledge, especially when they share physical infrastructure such as in business incubators, their learning and knowledge exchange with established and larger organizations are even more interesting and equally important for both parties. Learning of larger organizations with startups is addressed by Steiber et al. (2021). Large organizations, with their complex organization structure, are often prone to reducing and even losing their entrepreneurial orientation and capacity to learn and change, leading to stagnation and decline in their performance. Startups could then come as a valuable source of new ideas and knowledge that could result in new innovations for large companies and cooperation possibilities for startups regarding the diffusion of their ideas and prototypes.
For that purpose, Steiber et al. (2021) provided an empirically grounded typology of interorganizational learning between large corporations and startups in terms of collaboration models. For instance, in interorganizational learning, emphasis could be on large corporations, which form units that get in contact with external startups to work on market innovations in terms of knowledge co-creation. Somewhat of a looser approach could be to invite startups to locate near large companies to make way for new opportunities and serendipitous discoveries. On the other hand, large corporations could establish incubators that could host internal or external idea providers or startups. Their ideas and prototypes can then be internalized and further developed in the large corporation or as a spinout venture. Incubators could also be formed on the short-term basis (sometimes called internal corporate accelerators) and focused on strengthening the entrepreneurial orientation and spirit in a large company. On the other hand, large companies could establish networking platforms in which external idea providers and startup representatives are invited. When a large company is looking for partners to promote its innovations or is building an ecosystem, it can support the development of startup companies through a corporate startup program.
The general idea is that large organizations exploit exploratory capabilities of small entrepreneurial organizations. However, differences regarding size, value systems and goals could make this collaboration difficult. Differences in routines and attitude could hinder learning, knowledge transfer and its implementation, leading us back to the conclusion regarding the importance of practitioners and their mental models in interactions and integration of useful lessons learned.
Interorganizational learning in mainstreaming
Solheim and Moss (2021) address interorganizational learning in mainstreaming, which refers to the process of spreading information and knowledge about some ideas and values within a larger organization/system so that they become embedded in operations, or, in other words, that they become a behavioral norm. Solheim and Moss (2021) focus on gender mainstreaming in the complex organization – Swedish Ministry of Foreign Affairs, which governs the operations of embassies and consulates around the world but also has relations with other ministries. The purpose of the mainstreaming program was to contribute to overcoming of gender inequality between men and women in the organization’s operations. The idea was to stimulate learning on gender inequality and therefore to prevent it from being further reinforced and maintained in structures and systems.
Practitioners should note that for mainstreaming to produce a true learning process and result in the acceptance of ideas, there should be a cultural fit between the mainstreamed topic and the organization. If the two are not aligned, learning and change are not likely to occur. In addition, when engaged in mainstreaming, practitioners should look for ways to integrate mainstreamed ideas into existing practices rather than establish new ones. In other words, existing practices should be discussed through the prism of the mainstreamed ideas, which should in turn be implemented in the way to produce the greatest impact.
A coordination team could be appointed with the task to disseminate ideas and information and to help with issues such as policy development, structure design, communication, skill development to integrate mainstreamed ideas. The process should be supported by education, training, coaching and provision of materials indicating the importance of the implemented ideas. However, dialogue and joint sense-making that includes everyone involved should be a part of the mainstreaming process so that the ideas are not perceived as another indoctrination and/or new management fad. That could contribute to the development of shared understanding and common interpretative schemes (Lam, 2005) so that consensus is reached and new ideas start to permeate organization’s value creation process.
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This work is a part of the project “Development of management in the entrepreneurial economy and society” supported by the University of Rijeka, Croatia, grant number: 18–44 1174.