Solving task management conflict in hotel establishments through knowledge management tools: effects on innovation capabilities

Mario J. Donate (Department of Business Administration, Faculty of Law and Social Sciences, University of Castilla-La Mancha, Ciudad Real, Spain)
Fátima Guadamillas (Department of Business Administration, Faculty of Law and Social Sciences, University of Castilla-La Mancha, Toledo, Spain)
Miguel González-Mohíno (Department of Management, Faculty of Law, Economics and Management, University of Córdoba, Córdoba, Spain)

Journal of Knowledge Management

ISSN: 1367-3270

Article publication date: 19 May 2023

Issue publication date: 18 December 2023




This paper aims to analyze factors based on organizational knowledge management (KM; transactional memory systems and knowledge-oriented leadership [K-OL]) that help firms to mitigate conflicts based on task management at work, with the aim to improve their innovation capabilities (IC). The knowledge-based view of the firm, conflict management theory and cognitive collective engagement theory have been used to build a model of relationships that connects the development of positive KM contexts and management of dysfunctional conflict with IC improvement.


Data survey collected from inland hotel establishments in Spain is used to test seven hypotheses by means of structural equations modeling, applying the partial least squares technique. Direct, indirect and mediating relationships between variables are examined from the structural path model.


The results confirm that, as expected, IC improve when K-OL and transactive memory systems (TMSs) are properly implemented by hotel establishments, which leads them to reduce negative effects of task management conflict (TMC). Significant direct effects are found between the key variables of the study and also a significant indirect effect between K-OL and IC through TMS reinforcement and the mitigation of TMC.

Practical implications

This paper provides useful ideas for hotel managers about how to improve KM contexts in their establishments while avoiding TMC. Efforts devoted to creating those contexts by hotel establishments are shown to be effective to improve their IC and create competitive advantages.


The analysis of IC improvement by studying TMC mitigation had not been researched to date by the KM literature. The consideration and testing of a model that integrates KM-related tools such as K-OL and TMS to avoid TMC in the hotel industry is the main contribution of this study.



Donate, M.J., Guadamillas, F. and González-Mohíno, M. (2023), "Solving task management conflict in hotel establishments through knowledge management tools: effects on innovation capabilities", Journal of Knowledge Management, Vol. 27 No. 11, pp. 157-186.



Emerald Publishing Limited

Copyright © 2023, Mario J. Donate, Fátima Guadamillas and Miguel González-Mohíno.


Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at

1. Introduction

Conflict at work is one of the most impactful psychosocial factors in the quality of work life, organizational productivity and employee well-being (Roberts, 2005). Conflict is an inherent process of organizational dynamics and knowledge exchange discernible at interpersonal, group and organizational levels (Medina et al., 2005). As knowledge management (KM) processes lead employees at different levels of the organization to interact regularly and to bring together individual knowledge and skills at work (Donate and Guadamillas, 2015), conflict is likely to arise, as these interactions are influenced by personal, cultural and organizational structure-related factors (Donate et al., 2022). Moreover, effective knowledge processes should lead a firm to achieve its goals, among which the improvement of innovation capabilities (IC) is a major one (Donate and Sánchez de Pablo, 2015). An important issue that organizations must thus deal with is how to reduce or mitigate conflict related to KM implementation when IC are at the core of their competitive behavior. A special type of conflict, task management conflict (TMC), which originates from the design and implementation of tasks and processes at work (Jehn and Mannix, 2001) can be especially damaging for innovation as it can hinders creativity and organizational learning (Kianto and Andreeva, 2014). This research paper will focus on the analysis of solutions for TMCs in contexts in which innovation is a key issue.

To date, the importance of KM tools and practices has been underestimated as a solution to excessive conflict levels in conflict management research (Parayitam et al., 2021). Khan et al. (2022) assert that the availability of practices and knowledge-based principles to avoiding or reducing conflicts in innovative settings has rarely been analyzed in KM and innovation literatures. This is especially important for organizations needing to handle large amounts of data and information, which requires great efforts of coordination and learning for the development of highly complex, frequent and cooperative tasks and processes (Mentzas, 1993). To cover this gap, we propose two interrelated KM-based tools such as organizational transactive memory systems (TMS) and knowledge-oriented leadership (K-OL) as a solution to TMC, which results in an improvement of company IC. A TMS is a shared cognitive structure for the encoding, storage and retrieval of knowledge from different domains (Wegner, 1987). These collective repositories are useful to gain efficiencies when handling knowledge and information that are unevenly disseminated among individuals in the organizational sphere (Alavi and Leidner, 2001). A TMS supports KM processes of a firm by integrating individual and collective knowledge, making the adaptation to novel situations easier (Bachrach et al., 2019; Marques-Quinteiro et al., 2019). Moreover, employee awareness of the distribution of expert knowledge within the organization, along with the availability of appropriate tools to use and apply such knowledge, have been reported to be positively related to innovation (Marques-Quinteiro et al., 2019).

The second proposed KM tool is K-OL. This study establishes that the creation of a positive context to develop KM activities and build an advanced TMS for a company will strongly depend on the leadership style implemented at the organizational level. The literature shows that developing adequate specialization, coordination and credibility (a TMS’s dimensions) requires conscious efforts and guidance, direction and especially leadership toward a company’s goals (Hammedi et al., 2013; Moreland and Myaskovsky, 2000; Zhang and Guo, 2019). Donate and Sánchez de Pablo (2015) defined knowledge-oriented leadership as an organizational management style suitable for KM contexts, where there are strong pressures for knowledge sharing and exchange when a company needs to be highly innovative. This paper thus proposes K-OL as an antecedent of a TMS, being a main research goal the analysis of its impact on organizational IC by means of:

  • its contribution to the development of a sophisticated TMS; and

  • the reduction or mitigation of TMC in contexts where KM is an essential aspect for innovation.

Our theoretical contribution is based on the use of a knowledge-based view of the firm (TMS development by means of KM mechanisms) and a cognitive–collective engagement approach (Fachrunnisa et al., 2020) to explain how an excess of dysfunctional TMC can be mitigated by eliciting KM support based on transformational, transactional and communicational aspects of leadership.

Moreover, all these factors have not been jointly analyzed to date in the context of the hospitality sector, which will be a main contribution of this research study. Although the K-OL style has already been studied in the hotel industry by examining its effects on individual KM behaviors and work attitudes (Shamim et al., 2019), we offer two main novelties regarding this research line:

  1. We focus on the organizational level of hotel establishments, stressing innovation capability development as a performance measure of competitive advantage from a strategic point of view.

  2. The integration of different organizational KM artifacts in a model that tries to explain how to mitigate conflict by creating positive contexts for dialogue, knowledge sharing and collective engagement.

This industry is service-oriented, being very important for its sustainability the development of new initiatives reflected in services and processes improvement (Datta and Singh, 2018; Tajeddini and Trueman, 2012). Changes in cultural values (e.g. social and environmental demands), recent events (e.g. the Covid-19 pandemic) or the access to new platforms and information availability (e.g. social networks) involve new ways for firms to serve customer demands all over the world. Although KM tools can help hotel establishments to deal with task complexity and novelty, the pressure to deliver quality services can cause emotional exhaustion and conflict, which can negatively affect knowledge sharing and innovation (Khan et al., 2020). In addition, the hotel industry faces the problem of high staff turnover (Karatepe and Olugbade, 2009), so solutions based on KM by developing effective TMSs can support companies to retain, organize and accumulate human and organizational capital.

To summarize, the main contributions of this paper are the following:

  • to build an integrative framework to analyze solutions for excessive TMC based on KM-related tools (TMS and K-OL), aspect not analyzed to date by KM literature;

  • to investigate the effects of these organizational context factors to facilitate the development of IC in the hotel industry, which connects KM “artifacts” to the mechanisms for competitive advantage development (capabilities) based on innovation; and

  • to offer, from a practical perspective, guidelines to hotel establishments managers about how to apply solutions based on KM to mitigate TMC in workplaces, making their establishments highly innovative.

Overall, this paper advances the literature on the connection between KM and innovation by proposing an integrative model where, from a knowledge-based view, conflict management and cognitive–collective engagement theoretical perspectives, shows how the creation of a positive context based on KM tools has a key impact on dysfunctional TMC, allowing employees to share further knowledge and ideas for innovation capability improvement.

The structure of the paper is as follows. First, we develop the theoretical background and formulate the hypotheses of the paper in Section 2. Second, we explain the study methodology and test the model of the research in Section 3. Third, the results of the statistical analyses are shown in Section 4. Finally, we discuss the results and depict the conclusions of the study, along with its main limitations and possibilities for future research in Sections 5 and 6, respectively.

2. Theoretical background and hypotheses

2.1 Task management conflict and innovation in knowledge management contexts

In the past decades, KM has been perceived by companies worldwide as an organizational approach used to improve their internal processes while supporting business and corporate strategies (Bibi et al., 2021). From a knowledge-based view of the firm, knowledge is considered as a strategic asset, and thus, a source of competitive advantage, especially when is linked to innovation (Nonaka and Takeuchi, 1995). Based on the principles of KM, organizations try to improve the efficiency of business processes, increase the quality of their services and find new solutions for their customers’ needs (Donate and Guadamillas, 2011). More and more companies rely nowadays on KM technologies to assist employees in developing job assignments by improving communication, the exchange of ideas, the facilitation of interaction and knowledge sharing, while avoiding counterproductive behaviors such as knowledge hiding (Donate et al., 2022). Nevertheless, employees do not always understand how KM tools can help them to improve tasks efficiency, or they are not even aware of their availability in the company (Kundapur and Rodrigues, 2012). The employees’ vision to handle difficulties and conflict that arises from work duties might thus be constrained when these tools and their functioning in organizational activities are either unrecognized or misunderstood. Moreover, knowledge can be tacit, and sometimes personal, making it difficult to be “captured” and “encoded” for its organizational use in work tasks (Grant, 1996).

Conflict at work can be defined as the existence of grievances and disputes due to work and task development between employees and their supervisors, between employees and between different groups of employees (Currie et al., 2017). Excessive conflict and its ineffective management reduce the quality of work-life and organizational productivity from a psychosocial point of view (Babalola et al., 2018; Roberts, 2005). Jehn and Mannix (2001) define three categories of conflicts in organizations:

  1. relationship conflict, generated by personal disagreements;

  2. task conflict, resulting from disagreements about the content and results of the task being performed; and

  3. process conflict, caused by disagreements about how the tasks are performed.

The present study examines task and process conflicts in tandem, which we are tagged as TMC, with an emphasis on the context around work design and its implementation. Existing methods, procedures, technology and systems based on KM now heavily influence such a setting, particularly as knowledge sharing and its application are critical features for companies to effectively develop new products, services and processes (Zia, 2020). Work task design and implementation in companies are therefore inextricably tied to KM, and the availability of KM artifacts is likely to affect the degree of conflict, employee perceptions of conflict resolution and even the willingness to solve conflicts. Although individual and group interactions can have an impact on task and process conflict, this paper focuses on knowledge-based and collective work engagement theories to examine work conditions and organizational “tools” that can explain TMC mitigation at an organizational level for the improvement of a company’s IC.

The literature on organizational conflict generally agrees that a moderate level of TMC can often be beneficial to an organization (e.g. by fostering the exchange of ideas and showing various perspectives on how to handle a problem), but it can turn into unproductive as a result of persistent and intense disputes about assignments, design and task content (Afzalur Rahim, 2002; Zhu et al., 2016). Task-related conflict also occurs more easily when the frequency and need for interaction between employees is high (Gagné et al., 2019). Tense arguments about tasks may propel employees into a disturbed state of mind, breeding negative feedback and even rebellious behavior (Liu et al., 2013). In KM settings, the need to exchange and integrate knowledge, data and information to respond quickly to customer needs, along with the availability of advanced technological systems, makes the existence of TMC regarding KM a problem that firms need to solve when conflict reaches an excessive level that is not compatible with the goals and culture of the organization.

The literature that analyses the task conflict–creativity duality asserts that conflicts about how tasks are designed and implemented in the organization may cause alternative cognitive perspectives to be confronted, favoring divergent thinking and creativity by showing that there are different means to achieve the same goal (Petrou et al., 2019). While traditional conflict management theory considers people involved in conflict situations as troublemakers, modern theory shows conflict as a natural and inevitable outcome of human interaction, so conflict situations often lead to the generation of new ideas and change (Afzalur Rahim, 2002). A moderate level of TMC can thus lead employees to re-analyze their tasks, rethink the status quo and eventually find innovative solutions (Hülsheger et al., 2009). Nevertheless, a high level of conflict would reduce the motivation of workers to work as a team, which negatively influences the possibility of developing creative solutions to problems (Anderson et al., 2004). Conversely, the absence of task conflict does not seem recommendable, as a certain level of confrontation encourages discussion and the exchange of ideas, improving innovation processes (Petrou et al., 2019). When employees are not exposed to different ways of dealing with a problem, it is difficult for them to challenge pre-established assumptions to develop creative solutions (Perry-Smith, 2006). Organizations exploring opposite views and considering different alternatives for conflict resolution are able to improve the quality of decisions and generate further creative ideas (Somech, 2006).

Considering that moderate TMC can have a beneficial effect on IC, but excessive levels can be detrimental, this paper proposes an inverted U-shaped relationship between both variables, being conflict positively related to innovation up to a point where innovation starts to decrease. Moderate levels of TMC would thus positively be related to IC, but high levels would negatively affect innovation. We thus formulate the following hypothesis:


The relationship between TMC and IC follows an inverted U-shaped curve, where moderate levels of TMC are positively related to IC development up to a maximum point where TMC level increases in such a way that is negatively related to IC development.

2.2 Transactive memory systems to mitigate task management conflict

A TMS is a shared understanding of which a group’s members know and are responsible for Wegner (1987), containing three dimensions:

  1. specialization, which refers to knowledge about each group member’s specialized knowledge;

  2. credibility, which refers to beliefs about the reliability of other members’ knowledge; and

  3. coordination, which is the process of effectively coordinating knowledge between team members.

The TMS concept focuses on explaining how the expertise is recognized and coordinated within teams and leads to shared interpretations of the information available to team members (Lewis, 2003). A TMS is thus a collective cognitive structure endowing a group of people (teams, other work groups or the organization) with capacity to store, retrieve, discard, structure and integrate knowledge at the individual level to find effective solutions for the design and development of tasks and activities of the company (Wegner, 1987).

Current research on TMSs suggests that an organization shows a more advanced level of its TMS when there are high levels of knowledge specialization, credibility or trust in personal knowledge and coordination, due to the existence of systems, procedures and networks for the integration of knowledge (Heavey and Simsek, 2015). Moreover, there are factors that inhibit, or, on the contrary, facilitates the development of an effective TMS, such as communication (quality and frequency) and social and cultural values (for example, group identification or cognitive social capital) (Lavelle et al., 2022; Peltokorpi and Hood, 2019). But further research is needed to investigate how effective TMSs are related to KM contexts as facilitators of tasks development and performance variables such as innovation.

The management of work tasks can become highly complex for an organization when it is necessary to integrate and use advanced tools, resources and processes based on KM (Alavi and Leidner, 2001). In the absence of an advanced TMS, incompatibilities leading to excessive levels of conflict are likely to be more frequent because:

  • employees may lack a precise understanding of the person (or groups) responsible of specific areas of expertise;

  • employees can have a lack of confidence in the experience and expertise of others; and

  • employees are likely to experience coordination problems related to locating, retrieving, or applying knowledge to task development (Hood et al., 2014).

Nevertheless, an effective TMS makes specialized employees to become experts in specific tasks due to continuous learning, avoiding problems about how and who should execute a particular task (Hood et al., 2014). Specialization would reduce conflicts (both in number and importance) owing to the possibility of simplifying decisions on the allocation of responsibilities and resources to tasks. Moreover, high levels of credibility make that a company’s employees can access and receive information with lesser need to verify sources, which makes cost of verification to be reduced (Lewis, 2003). Trust also positively evolves when employees execute tasks effectively (Badrinarayanan et al., 2011). When levels of TMC are low, organizational members have the opportunity of showing their abilities, being able to generate trust to others (Chang, 2017). Finally, coordination facilitates team communication to articulate plans, define responsibilities, negotiate deadlines and share information to develop common activities (Rico et al., 2008). Poor coordination generates errors in knowledge articulation and codification, gathering and retrieval (Lewis, 2003), leading employees to have difficulties for retrieving and sharing requested information (Hood et al., 2014). These mistakes in knowledge retrieval involve information biases that lead employees to misinterpret previous task design and execution, which can degenerate in excessive TMC.

Therefore, companies developing advanced TMSs can support employees to become tasks experts by improving specialization, to generate a positive environment where they can trust their team colleagues and to make coordination easier for teams and individuals at the organizational level. From a conflict management theoretical perspective, a TMS would involve, following Afzalur Rahim (2002, p. 208), the design of an effective macro-level strategy to minimize the dysfunctions of TMC to enhance learning and effectiveness in the organization. By building this TMS, a company will be able to maintain a low level of TMC or will reduce it when its level is high. We thus formulate the second hypothesis of this research as follows:


The higher the level of development of an organizational TMS, the lower the level of TMC.

2.3 Knowledge-oriented leadership and transactive memory systems

The use of KM tools by organizational members to achieve a company’s goals is not always easy within a firm (Donate and Guadamillas, 2011). Moreover, the employees of an organization are not always able to take full advantage of these tools (and the company’s approach to KM) as, from a cognitive perspective, they may not be willing to spend time learning to use them or may not perceive that KM tools will contribute to improve tasks efficiency (Kundapur and Rodrigues, 2012). Companies should thus try to change employee behaviors toward KM through leadership, to make KM tools fully visible and support their successful usage (Singh, 2008).

Organizational leadership contributes to inspire employees to accomplish high-demanding work tasks (Lian and Tui, 2012). Regarding KM, leaders should be actively committed to supporting knowledge and learning activities while avoiding negative behaviors that threaten knowledge transfer, sharing and application (Cooke et al., 2014). Based on the knowledge-based theory, Donate and Sánchez de Pablo (2015) introduced the knowledge-oriented leadership (K-OL) concept to explain the importance of leaders as facilitators or even creators of “positive” contexts in which KM practices and activities could be carried out by employees effectively. This leadership style combines traditional transformational and transactional leadership types (Bass and Avolio, 1996), and it is also characterized by a communicative approach regarding the expectations of employees and a company’s goals (Donate and Sánchez de Pablo, 2015). Shamim et al. (2019) add that a K-OL is an attitude that includes consulting, support, stimulating knowledge dissemination, delegation, facilitation, mentoring, recognition and an innovative role modeling in the company. In addition, it provides a common vision, and rewards for knowledge sharing and intellectual stimulation, which pushes employees toward a change in thinking regarding learning and KM, and the collective results derived from the application of knowledge (Zia, 2020).

From a TMS point of view, developing adequate specialization, coordination and credibility requires conscious efforts and guidance, direction and especially leadership, based on the knowledge goals of a company. K-OL is thus considered in this paper as a highly relevant antecedent of a TMS, helping the firm to develop cognitive specialization, credibility and knowledge coordination. For example, knowledge-oriented leaders facilitate job assignments based on experience and expertise (Hammedi et al., 2013). Knowing who has specific skills (specialization) allows the rest of team members to find information and tasks allocation more easily (Moreland and Myaskovsky, 2000; Zhang and Guo, 2019). In addition, knowledge-oriented leaders can create safe and trustworthy environments, where employees are willing to share knowledge for innovation purposes (Donate and Sánchez de Pablo, 2015). Moreover, knowledge-oriented leaders facilitate the quality and frequency of communication, which academic research has been found to be an important antecedent of effective TMSs (Peltokorpi and Hood, 2019). Finally, organizational members need to coordinate tasks, which it is easier to develop when individual expertise about “what” and “how” is known by the organizational members (Lewis, 2003). In this case, knowledge-oriented leaders can provide active communication channels and information through which employees can deepen their understanding about the experts, even creating a common specialized terminology (Hansen et al., 2005) and information redundancy (Nonaka and Takeuchi, 1995). We establish, therefore, that when a company has a greater inclination toward the adoption of a K-OL style, the development of an organizational TMS is more strongly encouraged. We thus formulate the third hypothesis of this paper:


The higher the level of adoption of a K-OL style by an organization, the greater the level of development of an organizational TMS.

2.4 The role of a transactive memory system as a mediating factor between knowledge-oriented leadership and task management conflict

Knowledge-oriented leaders can help a firm to identify and share information about the organization’s constraints and opportunities and provide an overview of the existing relationships in order to perform work tasks. Hence, they contribute to solve problems, allocate resources and help the firm to ensure that employees achieve performance goals (Shamim et al., 2019). Due to increasing complexities and ambiguities that arise in workplaces in relation to knowledge integration, leaders can have difficulties to perform many of their roles, due to limitations in technical information or experience regarding followers (Singh, 2008). In this context, K-OL is thought to be supported by the effectiveness of a TMS for task design and implementation, especially when there are significant requirements for interaction between members of groups to share and integrate knowledge, which can cause an increase on organizational conflict. Knowledge-oriented leaders can thus positively influence work commitment and cognitive processes linked to employee creativity, mitigating conflicts and improving the search of creative solutions (Shamim et al., 2019).

Even when K-OL can have a direct, negative relationship with TMC, this paper also posits that this connection is mediated by the development of an effective TMS. When conflicts and disagreements about tasks and processes exist, communication and guidance to alleviate those conflicts from a KM perspective can come from leaders (Wu et al., 2017), but those actions are also channeled toward solving conflicts by affecting specialization (e.g. employees who can help to solve the conflict by using a KM tool), credibility (e.g. trust in a group member involved in a KM system) and coordination (e.g. how to use properly a KM tool or system). K-OL can thus affect TMCs by:

  • offering direct support to mitigate or reduce them by using direct communication and transactional leader-follower actions from a conflict management perspective;

  • exerting indirect effects on the communication and organization of tasks, transformational leader-follower actions and the development of a “positive” context by facilitating creative dialogue about task design and implementation issues.

The second alternative would be based on a cognitive collective engagement approach (Fachrunnisa et al., 2020), in which trust created by knowledge-oriented leaders (the context) helps employees to engage in creative dialogue about task development and implementation, avoiding or mitigating an excessive level of organizational conflict.

The first alternative is essentially based on avoiding errors, saving time and adjusting task implementation by means of communication, supervision and incentives (Yang et al., 2014). This can be understood as an organizational-level strategy to avoid dysfunctional aspects of TMC (Afzalur Rahim, 2002). The second alternative connects K-OL to TMC through the development of an effective TMS from a “positive” collective-engagement perspective, attempting to improve performance by means of establishing highly routinized work in a context that avoids or improves problematic situations of TMC (Ohly et al., 2006). Both alternatives are not incompatible; they rather suggest a double mechanism by which K-OL affects TMC, reflected in the following hypotheses:


The higher the level of adoption of a K-OL style by an organization, the lower the level of TMC.


An organization’s TMS mediates the relationship between K-OL and TMC.

2.5 Indirect effects of knowledge-oriented leadership and transactive memory systems on innovation capabilities through task management conflict mitigation

KM and innovation literatures have analyzed in recent years the existing relationships of TMS and K-OL with innovation. In relation to TMSs, a major research line focuses on how they provide work groups with a structure and processes that allow them to both integrate knowledge to develop tasks effectively and generate and capitalize on new ideas for innovation (Zhang et al., 2020). TMSs help companies to develop routines that allow organizational groups to reflect on problems and recalibrating tasks by suggesting creative solutions (Marques-Quinteiro et al., 2019). These routines and tools also prevent employees from becoming frustrated and unwilling to participate in the exchange of ideas.

As we established previously, an effective TMS is likely to have an impact on TMC, reducing or avoiding an excessive level of conflict when tasks are performed, as knowledge specialization, credibility and coordination create a positive context to share and integrate individual knowledge and resources. But we now predict that a highly developed TMS has also a relevant impact on IC through TMC mitigation. For example, the research on TMS-team innovation performance relationship reports a positive impact of the former on the later, being those studies generally developed to analyze R&D groups, with work tasks mostly oriented to develop ideas and implement them (Cabeza-Pullés et al., 2018; Peltokorpi and Hasu, 2016). Our argument is that although work tasks cannot be per se oriented toward developing new ideas (and their implementation), an effective TMS makes conflict tolerable to the limit of maintaining creative dialogue about how to improve tasks and related processes, which will indirectly improve IC (i.e. new processes development, new services deployment). Moreover, an effective TMS would help the firm to avoid “knowledge hiding” or opportunistic approaches to knowledge (e.g. knowledge hoarding), and, in this sense, it would improve the company’s ability to innovate by allowing employees to share knowledge (Donate et al., 2022). Conflict management theory and the knowledge-based view of the firm would thus be intertwined to explain the positive development of IC based on TMC mitigation and its impact on a TMS’s knowledge dimensions. IC would be improved by avoiding the negative effects of TMC (e.g. not to share knowledge) and by the positive effects of TMS (e.g. knowledge sharing and creation). We thus hypothesize an indirect impact of TMS on an organization’s IC via TMC mitigation by formulating the following hypothesis:


A TMS has an indirect effect on the development of an organization’s IC through its influence on TMC mitigation.

Finally, and regarding the effect of K-OL on IC, the existing research suggests that although there is a significant impact of the first variable on the later, this is normally indirect, by acting on intermediate (or even moderating) variables that ultimately improve company innovation (Donate and Sánchez de Pablo, 2015). From a conflict management and knowledge based-view theoretical perspectives, Bai et al. (2016) indicate that conflicts derived from work tasks design and implementation could contribute to the exchange of knowledge and creativity of employees by triggering an exchange of information and an exploration of diverse and even opposing opinions. However, the level of task conflict can become so intense that information processing can be blocked (De Dreu, 2006).

The last hypothesis of this study thus establishes that K-OL has a significant impact on IC through the indirect effect caused by the development of an advanced TMS, and subsequently, through TMC mitigation. We specifically propose that, although K-OL does not eliminate problematic TMCs directly, it will reduce them to a level where they can positively affect IC through TMS development, helping the firm to clarify, coordinate and assign tasks among workers and manage conflicts that arise from their performance. On the one hand, those characteristics that define K-OL, such as its transformational perspective, allow the firm to have a critical vision of tasks, which enriches the debate about their correct performance (design and implementation). On the other hand, its transactional perspective helps company members to avoid an excessive debate about designing and implementing the different tasks, especially those related to KM. We thus propose that K-OL positively influence IC indirectly, first through its direct effect on a company’s TMS development, and second (indirectly) on TMC, through the creation of a positive context for innovation. We thus establish the following hypothesis:


The higher the level of adoption of a K-OL style by the organization, the greater the development of its IC, but this effect is indirect, caused by its positive influence on the TMS and a subsequent mitigating effect on TMC.

We summarize all the hypothesized relationships in a conceptual model, which is reflected in Figure 1.

3. Methodology

3.1 Research context

The context of our study is provided by inland hotels in Spain. Available studies (Institute of Tourist Studies; Spanish Statistics National Institute; World Tourism Organization) show a growing demand for inland hotels due to a favorable environment (before the COVID-19 pandemic): a growth in leisure time; an advance in the retirement age; higher education level; and an increasing demand for cultural events. The increasing demand for nature, culture and business-related events has also strengthened inland tourism in Spain in recent years, in comparison to the traditional “sun and beach” vacation model (Varela and Martín, 2011).

Work tasks in the hotel industry are characterized by a high level of pressure (Kim et al., 2009). Research has shown that stress at work comes from factors such as excessive workload (Karatepe and Aleshinloye, 2009), long-lasting and irregular working hours (Zhao et al., 2014) and the difficulty to reconcile work and family life (Choi and Kim, 2012). Stress can cause low job satisfaction and well-being levels and distress (Salas-Vallina et al., 2021). As noted in previous sections, existing research has generally shown that conflict has a positive association with stress and emotional exhaustion (Yoon et al., 2010) and the negative attitudes and behaviors of hotel employees can have an important effect on customer satisfaction and loyalty (Lin et al., 2013). From a KM perspective, employee knowledge is one of the most important resources in service firms, and it is particularly significant to perform activities that require interaction, collaboration and communication with customers (Nieves et al., 2014). In the tourism industry the improvement of human capital has become a priority, as knowledge is actually located in the minds of individuals rather than in technologies, structures or routines, and the risk of losing organizational knowledge is high, due to staff turnover (Argote and Ingram, 2000). It is thus essential for the organization to be able to take advantage of knowledge that is embodied in individuals to build a corporate knowledge base and IC (Nieves et al., 2014). For example, operational routines for managing specific customer needs involve smooth knowledge sharing and the integration of abilities to respond timely (e.g. coordination of business or conferences events, organizing group cultural trips, etc.). Hence, TMC involving (not) knowledge sharing is especially risky for hotel establishments. Moreover, in the past few years, the hotel sector is developing into a highly knowledge-based industry owing to recent advances in information processing that allow hotel establishments the extensive use of knowledge transfer, reuse, storage and application (Kim et al., 2021). Therefore, it appears to be a suitable industry for the analysis of TMC and factors for its mitigation based on KM approaches and tools, such as K-OL and TMS for the development and improvement of IC.

A questionnaire was designed to collect information on K-OL, TMC, TMS and IC of inland hotels in Spain, and subsequently administered through an online survey, open from December 2017 to October 2018. We only selected hotels from major cities in inland Spanish provinces (a total of 28), as our goal was to consider establishments with similar challenges and needs, and services offered to customers (e.g. culture, leisure, business tourism). The search strategy was based on the website, following recent research (Cantallops and Salvi, 2014; Kwok et al., 2017; Nicolau et al., 2020), along with the consideration of the Hosteltur database (a Spanish consultancy company specialized in the hospitality sector). An ad-hoc database was created with information from every hotel in our final population (767 inland hotel establishments).

The questionnaire was directed to hotel employees who were responsible for a team or a group of workers (e.g. reception services, human resources or administration managers) of three-to-five-star hotel establishments. These employees are an essential link between a hotel’s senior management and front-line employees (Kuo et al., 2012). They also play a key role in providing new services and process innovation, as they can collect ideas from front-line employees, and at the same time, supervise task development and KM activities. The 767 inland hotels were contacted by e-mail and phone calls. We finally collected responses from 118 hotels, representing 15.38% of the total population under study. Management literature considers acceptable a response rate between 10% and 20% in survey studies, due to the low incentive for respondents to answer the questionnaire and the difficulty to get access to the firm’s managerial team (Chow and Chen, 2012). The technical information of the research is included in Table 1.

The validity of the questionnaire was assessed through the calculation of the intraclass correlation coefficient (ICC) for the main variables of the study (Fleiss, 1986), using IBM SPSS software. Two or more questionnaires for the same hotel establishment (different respondents) were collected in ten cases (40 total respondents). The ICC for K-OL was 0.851, for TMC 0.904, for TMS 0.749 and 0.925 for IC. Shrout and Fleiss (1979) established the threshold for acceptable values in 0.70.

Regarding concerns about method common biases, the following remedies were used to alleviate them. First, the study offered anonymity about independent and dependent variables to the respondents by using multi-item scales without a reference to the constructs. Moreover, the complex data relationships based on indirect and mediating effects that we propose in this study helped to alleviate possible common method bias concerns, as the respondents were unable to guess the research hypotheses or respond in a socially desirable manner when they were completing the questionnaire, which would lead to spurious findings (Ko et al., 2021). From a statistical viewpoint, a Harman’s test was also applied to the questionnaire variables to assess the existence of common method bias for the data set. An exploratory factor analysis (principal components with a varimax rotation) was performed by considering the four main constructs of the model (K-OL, TMC, TMS and IC), with results showing the existence of seven factors with eigenvalues above 1, explaining 72.3% of the total variance. As only 30.1% of the total variance is explained by the first factor, common variance does not seem to be a significant concern for the research (Podsakoff and Organ, 1986).

The response by category (number of stars) within the hotel industry was consistent with the percentage that each category presented concerning the target population. Table 2 shows the number and percentage of responses for each of them, along with other descriptive variables for the hotel establishments included in the study sample. Moreover, and to check for sample representativity regarding size (number of rooms) we ran a T-test to analyze differences between hotel establishment respondents (the sample) and the total population, which showed a non-significant result (t = 0.723; p = 0.87).

3.2 Measures

All the construct measures were adapted from the existing literature. Rigorous data checking was applied, along with the validation of measures. A pre-test was also developed, which allowed us to obtain more than one respondent for 10 hotel establishments and check the readability and understanding of the items. Subjective Likert-type scales were used (see Appendix) to measure the study variables, with items ranging from 1 (strongly in disagreement) to 7 (strongly in agreement).

3.2.1 Knowledge-oriented leadership.

To measure this leadership style, six items were considered, containing elements of leadership based on both transformational and transactional styles (Bass and Avolio, 2000; Bryant, 2003) linked to KM. Items relating to motivation and communication with employees were also included in the measurement. This scale has recently been developed by Donate and Sánchez de Pablo (2015) and used to analyze the effect of K-OL on innovation with KM practices acting as mediators, being also used with slight adaptations in other KM contexts (Fachrunnisa et al., 2020; Zia, 2020). All the questions were set out at the organizational level; that is, they were referred to the management style being implemented in the company (in this case, the hotel establishment). For example, an item was the following: “the management style implemented in the hotel establishment has created an environment for responsible behavior, teamwork, and knowledge sharing.” Cronbach’s α of the scale was 0.832.

3.2.2 Task management conflict.

TMC was measured by employing a multi-item scale adapted from Jehn and Mannix (2001) intragroup conflict measure, using six indicators expressing task and process conflict. The scale was also adapted to the organizational level rather than being referred to a specific group or team in the company. An item of this scale is: “there are frequent disagreements about who should perform specific tasks in workgroups.” Cronbach’s α of the scale was 0.918.

3.2.3 Transactive memory system.

A modified version of the scale proposed by Heavey and Simsek (2015) and made up by 15 items from a previous version designed by Lewis (2003), was used in this research to measure the level of development of a TMS by the hotel establishment. The latent construct is made up of three dimensions: specialization, credibility and coordination, each of which includes five specific items. Following Lewis and Herndon (2011) and Heavey and Simsek (2015), we consider this concept as a second-order construct, in which the three dimensions are formatively integrated into one single indicator. An item of this scale is (for specialization) “every hotel employee has unique experience in specific areas of activity.” Cronbach’s α for specialization was 0.774, for credibility 0.810 and for coordination 0.813.

3.2.4 Innovation capabilities (new services and processes).

We selected a measure of IC based on the development of new or improved services and processes in hotel establishments. In the hospitality industry, process innovation can reduce work or delivery times and help an establishment to diminish operating costs. It can also improve the quality of processes by which services are delivered (Damanpour, 2010), even changing how an organization develops new services (Bessant et al., 2005). This paper considers process IC as a measure of innovativeness in hotels because it plays a central role in organizational performance, as it is connected to sustainable competitive advantages (Porter, 1985). Likewise, IC in services were also considered, as the introduction of new services is necessary for the adaptation to changing environments and as a differentiation posture for a firm. A scale of 11 items developed by Tuominen and Hyvönen (2004) was used to measure the construct (5 items for innovation service capabilities, 6 items for process IC), being adapted to the context of hotel establishments. An item of this scale was: “In the last year, the hotel establishment has introduced more services (new or improved) than its main competitors.” Cronbach’s α of the measure was 0.941.

3.2.5 Control variables.

This study considered hotel size as a control variable, measured by the total number of rooms and transformed to a logarithm scale. We considered size as a variable connected to innovation, as it is likely that the larger the hotel establishment is, the higher the number of interactions between employees to develop process and service innovation will be (Donate et al., 2016). Moreover, larger hotels have also bigger budgets than smaller hotels to introduce novelties, technologies and new services; thus, we expected a positive influence on IC. Additionally, the hotel category was considered (three, four and five stars), for which two dummy variables were constructed, considering three stars hotels as the reference variable. We expected that the higher the category, the higher the tendency to be innovative, as the range of offered services tends to be larger (Madanoglu and Ozdemir, 2016). Finally, the hotel property was also considered. Hotel chains can share innovation in processes developed in different locations (Wikhamn, 2019). It is also likely that the approach to innovation is different for hotel chains than independent establishments (for example, innovation strategies could be planned in corporate headquarters), and hence IC could be different for these two types of hotel establishments.

3.3 Statistical methods

A structural equations model (SEM) was used to test the hypotheses through the partial least squares (PLS) technique, which was selected based on two considerations. First, the model was established with a predictive goal, which fits in with the goal of PLS as a statistical tool (Hair et al., 2017). Second, the size of the sample was not too large, so PLS is a proper method to calculate parameters of a path model as the estimation is based on variance rather than covariance matrices (Hair et al., 2017). The software used to perform the analyses was SmartPLS 4.0 (Ringle et al., 2022). The SEM analysis using PLS follows a two-stage approach:

  1. measurement model analysis; and

  2. structural model analysis.

Both stages and results are explained in the following section.

4. Results

4.1 Measurement model

All the constructs of the study were considered as reflective (first order) due to their expected unidimensionality, except TMS, typically integrated by three dimensions: specialization, coordination and credibility. Thus, it has been considered in this study as a formative construct. Unlike reflective indicators, where high correlations between the indicators are desirable as they refer to the same concept, in formative constructs each indicator (dimension) explains a specific aspect of the latent variable, being complementary to the rest of dimensions, so the correlations between the indicators are moderate (Diamantopoulos and Winklhofer, 2001).

Table 3 shows the resulting figures for the validity of the reflective constructs (first order). Convergent validity and composite reliability tests reveal acceptable loading factor values, with Cronbach’s alphas always above 0.70, average variance extracted (AVE) values above 0.50 and RHO values above 0.70 for every variable. Previously, the item K-OL4 was removed, as its loading was below the minimum recommended threshold level of 0.6 (Falk and Miller, 1992). The discriminant validity for all the latent variables was also assessed by the Fornell–Larcker criterion and Heterotrait–Monotrait (HTMT) relationships. Table 4 shows both tests, with all the values above 0.7 in the main diagonal (Fornell and Larcker, 1981) and HTMT values below 0.9, which fulfill the recommended general rules (Hair et al., 2014).

This study used a two-step approach to build the formative TMS construct, which was first connected to the latent variable itself. We then used bootstrapping (5,000 subsamples) to assess the indicators’ loadings, deleting the items TMS2, TMS9 and TMS15, as they all were below the threshold of 0.6 (Gefen and Straub, 2005). Table 5 shows the analysis of the validity and reliability of the formative construct. We analyzed, on the one hand, the collinearity between the components (through the variance inflation factor [VIF]), with all the components showing acceptable values (VIFs between 1.58 and 1.84) and, on the other hand, the weights of each dimension (β) regarding the formative construct, which were all significant with p < 0.001 (coordination 0.393, credibility 0.381 and specialization 0.814) [1].

4.2 Structural model

To assess the structural model, we calculated the path coefficients or standardized regression weights (β). The structural model validity is usually checked by means of the significance levels of the path coefficients and the R2 values for the dependent variables.

A bootstrapping (5,000 samples) was run to generate the Student’s T statistics and the standard errors for the calculation of the statistical significance of path coefficients. Table 6 shows the quadratic, direct and indirect statistical relationships between variables. The results exhibit significant relationships for all the paths, except the quadratic relationship between TMC and IC and the direct relationship between K-OL and TMC.

Nonlinear effects (quadratic) were calculated by using the SmartPLS algorithm by following a two-step approach (Hair et al., 2017), which uses the latent variable scores from the predictor variables of the direct effects model (without the quadratic effect term). These latent variable scores are saved and used to calculate the quadratic indicator applied in the second step of the analysis, by adding the quadratic effect term in addition to the predictor variable. As shown in Table 6, the quadratic effect of TMC on IC is not significant (β = 0.152, p > 0.05), so H1 is rejected. Hence, the relationship between TMC and IC does not appear to follow an inverted U-shaped pattern, but a rather different relationship.

Regarding the direct effects, H2 and H3 are supported, as coefficients are both significant. Thus, the adoption of K-OL has a positive and significant effect on TMS in hotel establishments (β = 0.611; p < 0.05). Therefore, a K-OL style helps establishments to develop a TMS. Moreover, the relationship between TMS and TMC has a negative and significant effect (β = −0.332; p < 0.05), meaning that the higher the level of development of a TMS in hotel establishments, the lower the existing level of TMC.

Moreover, the effect between K-OL and TMC is not significant in the global model (β = −0.128, p > 0.05), so we reject H4. Nevertheless, the indirect effect (the impact of K-OL on TMC through TMS) is negative and significant (β = −0.203, p < 0.05), and the variance accounted for, which shows the strength of the mediation by indicating the value of the indirect effect of the two variables in relation to the total effect (Nitzl et al., 2016) is 0.61. We also ran a Sobel (1982) test following the recommendation of MacKinnon (2008). This test indicates whether the indirect effect of the independent variable on the dependent variable through a mediating variable is significant. The Sobel test statistic (z score) for our mediating relationship was 3.008, with p < 0.05 (one-tailed). The significant result confirms the effect, so a mediation relationship of TMS between K-OL and TMC exists and H5 is thus supported. Moreover, the fact that the original parameter for the relationship between K-OL and TMC was significantly reduced when the TMS variable was introduced into the model, even resulting as non-significant, make us to consider that the mediating effect is close to total rather than partial (the original correlation between K-OL and TMC is −0.331, with p < 0.01).

Regarding the indirect effects, first, the impact of TMS on IC through TMC mitigation shows as positive and significant (β = 0.181; p < 0.05), so H6 is supported. TMS has thus a positive influence on IC development by means of TMC reduction. Likewise, the indirect effect of K-OL on IC via TMS development and TMC mitigation is also significant (β = 0.111; p < 0.05), so H7 is also supported, meaning that the more a company adopts a K-OL style, the more the development of IC, but by acting directly on TMS development, and indirectly, on TMC mitigation. Moreover, size (measured through the natural logarithm of the number of rooms in hotel establishments), considered as a control variable, is significantly connected to IC (β = 0.165, p < 0.05). The larger the size of the hotel establishment, the higher the level of development of IC. The rest of control variables did not show significant effects in relation to IC, neither hotel category (β = 0.069, p > 0.05) nor type of property (0.077, p > 0.05), so they are not shown in Figure 2.

We also analyzed the relevance of the predictive model through the R2 value for every dependent construct. According to Falk and Miller (1992), these values must be at least equal to or greater than 0.1 to consider that the model has enough predictive capacity. In our case, all the R2 values are above 0.1 (Table 7), so the model has enough predictive power. To additionally assess the model’s predictive relevance, we calculated the Stone–Geisser Q2 statistic. According to Chin (1998), the predictive relevance of a construct is relevant when the test offers values of Q2 > 0, condition which is fulfilled for the three dependent variables of our model (Table 7).

Finally, and following the recommendation by Hair et al. (2014), we analyzed conditions of robustness of the model. First, by checking the non-linearity of the established relationships. This was carried out by means of the calculation of quadratic associations (Basco et al., 2022), which was already applied for our H1. As indicated, that quadratic relationship between TMC and IC was non-significant (β = 0.152, p > 0.05). The rest of the direct relationships established in the model were all also non-significant: between TMS and TMC (β = −0.054, p > 0.05), K-OL and TMC (β = 0.024, p > 0.05) and K-OL and TMS (β = −0.045, p > 0.05). Second, we calculated Gaussian copulas (Gc), trying to detect endogeneity for the relationships in the structural model (Becker et al., 2022). All the Gc were not significant, with Gc for TMC and IC = −0,761 (p > 0.05), Gc for K-OL and TMC = 0.054 (p > 0.05), Gc for K-OL and TMS = −0.176 (p > 0.05) and Gc for TMS and TMC = −2.96 (p > 0.05). Finally, we cautiously assume homogeneity for the model as PLS-SEM literature recommends not to split the sample to check for heterogeneity (recalculation of the model for subsamples) when this is not too large in size (Hair et al., 2017).

5. Discussion

This research aimed to analyze organizational aspects related to KM, such as K-OL and TMS, which help inland hotel establishments to create a context that mitigates dysfunctional conflict, favoring innovation. The results confirm that K-OL can assist members of an organization with the management of conflicts by promoting the development of advanced TMSs. Implementing a K-OL style that promotes both clear KM vision and direction (“leading by example”), along with fluid communication, support and incentives for the use of KM tools appears to be appropriate to solve or reduce conflicts cooperatively; or in other words, by helping to create a favorable organizational context and collective engagement based on KM for innovation.

The results of the research stress a challenge that the current management of people, in a global environment, has for managers and organizational leaders: to maintain moderate levels of TMC in the organization to generate further innovation (De Dreu, 2006), as TMC can be harmful when it exceeds a particular level. Nevertheless, this study does not offer evidence that TMC follows an inverted U-shaped curve, contrary to recent research findings (De Dreu, 2006; Farh et al., 2010; Petrou et al., 2019; Shaw et al., 2011). In our study, the linear relationship between TMC and IC is negative and significant, showing that TMC harms IC for every level of TMC (β = −0.546, p < 0.01). De Dreu and Weingart (2003) also found this negative relationship between task conflict and both team performance and team satisfaction in a meta-analysis study, which is consistent with a perspective of “conflict information” that explains that task conflict interferes with cognitive flexibility and creative employee mindset, becoming thus a barrier for information exchange, processing and creative solving problems that ultimately harms IC in teams and organizations (Langfred and Moye, 2014).

This study has found that positive KM work environments containing high levels of credibility, specialization and coordination, can favor TMC mitigation (H2). The direct and negative effect between TMS and TMC arises as TMS helps the company (and teams) to manage activities, mostly complex and unpredictable, where the implicit coordination for task design, development and implementation can be problematic (Giebels et al., 2016). The results show that the greater the development of the TMS’s hotel establishment is, the lesser the TMC will be. Tasks are thus better designed and implemented when knowledge specialization, coordination and credibility are further developed, affecting TMC levels. This result concurs with the research of Littlepage et al. (2008), who showed that allocating specific tasks to the most competent employee (when members differ in abilities) leads to more effective utilization of the team member knowledge and higher team performance, while coordination and credibility helps the team to allocate work to the more proficient member without incurring in high levels of conflict. Moreover, an advanced TMS restricts conflictive situations, as information flows are limited before a task is implemented (Lee et al., 2020). Hence, knowing in a credible way who is the “expert” or the most competent person to develop a specific task, along with generating a common vision about the effectiveness of the subsequent coordination, generates a sense of acceptance about the allocation of specific roles and their coordination for tasks implementation.

The study also supports H3, which proposed a connection between K-OL and TMS in hotel establishments. A K-OL style allows a firm to make knowledge resources and tools highly visible for employees, breaking barriers of communication and contributing to enhance coordination and credibility, which in turn improves the development of a TMS and team cooperation. Zhang and Guo (2019) found a similar connection than our research, as the implementation of a K-OL enabled employees contact when knowledge diversity in terms of specialization was high in the organization, improving the performance of multifunctional projects, as communication barriers were overcome and cooperation encouraged.

Regarding H4, the proposed negative effect between K-OL and TMC was not significant. Nevertheless, when TMS was considered as a mediating variable, K-OL was indirectly connected to TMC (H5). Thus, a K-OL seems a necessary but not sufficient condition to reduce TMC. The sufficient condition is that K-OL contributes to TMC mitigation by means of a highly developed TMS. This type of leadership is oriented toward generating a positive predisposition to engage employees in processes, activities and KM tools and to reward (or sanction) the appropriate (or not appropriate) use of these elements (Donate and Sánchez de Pablo, 2015). The context created by this leadership style helps to reduce TMC, but rather through its contribution to the definition of knowledge specialities, the generation of credibility on internal knowledge agents and the contribution to the coordination of a company’s tasks, many of them linked to KM tools/processes such as those based on information and communication technologies systems (Zia, 2020). Moreover, a TMS is relevant when the team’s tasks require large amounts of information and knowledge (Lewis and Herndon, 2011), which is a main argument in the proposal of our research.

H6 was referred to the indirect effect of TMS on IC by means of TMC mitigation. While the existing literature points to a complementary role between a TMS and innovation, the role of TMC mitigation as an intermediate variable had not been studied to date. Our findings suggest that the development of a cognitive space in which a knowledge “map” about task specialization is shared by organizational members makes IC development easier for hotel establishments. In fact, a TMS offers a cognitive structure of each team member that makes knowledge sharing and cooperation easier by means of all the available knowledge stock in the organization (Ali et al., 2019). This shared and detailed knowledge about the employees’ specialization supplies a context and conditions to support creativity, collective engagement (Fachrunnisa et al., 2020) and innovation (Gino et al., 2010). The improved coordination can also improve information combination in novel ways (Wegner, 1987) and the implementation of creative ideas about tasks procedures and practices.

Finally, H7 proposed a link between K-OL and IC by means of TMS development and TMC mitigation, with results confirming a significant indirect effect. K-OL is thus shown as a key element to support the development of IC in hotel establishments. Other research papers have also found positive effects of a K-OL on innovation (Donate and Sánchez de Pablo, 2015; Naqshbandi and Jasimuddin, 2018; Zia, 2020), but our research is developed in a different context (hotel establishments) and we have suggested TMS as a channel through K-OL is able to improve IC though TMC mitigation. In a recent paper, Donate et al. (2022) analyzed the role of K-OL on IC, but the positive effect was generated by reducing organizational knowledge hiding. Hence, our paper contributes to KM and innovation literatures by adding TMSs to the factors that can be influenced by K-OL to improve IC. By motivating employees toward a KM perspective, knowledge credibility and team coordination are amplified, so TMC is less likely to arise (or at least, not to be increased extensively or in a dysfunctional manner). Organizational members will be encouraged to share and discuss ideas with others and this, along with the implications of a highly developed TMS on task management, will mitigate TMC, improving IC.

6. Conclusions

6.1 Theoretical contributions

Our proposed model contributes to the academic literature on KM and innovation in several ways. First, to our knowledge, this is the first model to explore the dynamics on how TMCs are reduced by means of TMSs, which includes the dimensions of knowledge credibility, coordination and specialization. Second, this study sheds light on how to manage TMC at the organizational level through tools and perspectives based on KM. The third contribution has been the study of a leadership style that allows hotel establishments to manage conflicts through TMSs to improve the development of IC at an organizational level.

This paper has stressed the importance of managing excessive levels of dysfunctional task conflict to avoid negative repercussions on a company’s IC. Conflicts can have consequences for mental health, such as stress and burnout, and to cause accidents, absenteeism and high turnover levels (De Dreu et al., 2004). From a psychosocial perspective of human resource management, individual well-being is considered a key factor to maintain employees motivated toward innovative behaviors, which will have an influence on collective IC (Muñoz et al., 2023). If we consider the Covid-19 pandemic and its effects on employees and firms around the world, the aspects related to wellness or employee well-being appear as essential factors having positive influences on company performance. Conflict attenuation should be reflected on positive behaviors which, in conjunction with a K-OL, would direct employees to search actively solutions to problems by using collaborative KM tools and perspectives.

Moreover, competitive advantages based on innovation depend on sources of capability development that are rooted in the collective engagement of organizational members (Fachrunnisa et al., 2020). This engagement allows firms to create and adapt routines and capabilities to remain innovative in highly dynamic contexts by sensing opportunities, seizing them and transforming the organization for their exploitation (Teece, 2018). From this evolutionary point of view, work tasks need to evolve by flexibly and quickly including new ideas and novelties to create new products, processes and services. In this regard, excessive levels of dysfunctional task conflict inhibit knowledge flows and slows down the pace of evolution of IC, which can make that a company falls behind industry competitors. K-OL has been highlighted as a theoretical construct coming from the KM literature that help companies to engage collectively their employees in tasks by enacting KM philosophy, collaboration and interaction via KM tools. Overall, a contribution of this paper has been to offer a conceptual model that predicts the strength of a company’s IC by promoting cognitive-collective engagement via K-OL implementation and TMS development. This type of leadership developed by means of practice and deliberated learning efforts would succeed in adapting routines for the design and implementation of tasks through the position reached by the TMS (regarding specialization, credibility, coordination level and creativity), which can be understood as a KM dynamic capability (Zollo and Winter, 2002).

Finally, the model also connects to the line of research related to the handling of unexpected situations and adaptative performance (Jundt et al., 2015), as TMS could be understood as a conceptual tool whose principles are rooted in the coordination of organizational behavior and relatively complex tasks in a semi-automatic manner (Lewis and Herndon, 2011). Research in this topic generally establishes that a relevant TMS is useful when group-level tasks require the processing of large amounts of information and knowledge, which has been a perspective used in this study applied to the development of IC (and the mitigation of excessive TMCs). From the knowledge-based view of the firm, IC come from the ability of firms to generate, combine, share, recover and apply knowledge to sense and seize new opportunities (Grant, 1996; Teece, 2018). These capabilities are the basis of sustainable competitive advantage in unpredictable and volatile environments such as those that most firms are facing nowadays.

6.2 Practical contributions

This study sheds light on appropriate leadership behaviors to improve IC in contexts where KM is a highly relevant aspect, such as inland hotel establishments. K-OL implementation makes the use of both tacit and explicit knowledge in the organization easier (Donate and Sánchez de Pablo, 2015). Hotel staff stay in direct contact with customers and continually receive information from them. If a leader can motivate employees to process this information, use KM tools more intensively and share tacit and explicit knowledge within the organization, it is more likely that IC can be developed to deliver superior services and achieve competitive advantages for these establishments.

This paper provides ideas for hotel managers in order to improve KM contexts in establishments while avoiding TMC by considering a K-OL and TMS mutual framework. By adopting this leadership style, employee behavior will be improved, being possible to enhance services quality and maintain customer satisfaction and loyalty (Kim and Lee, 2013). Moreover, when a management style such as this encourages open and transparent communication and formal and informal connections to share knowledge and ideas, a KM culture is developed in the organization. Such culture can create collective engagement, allowing employees to discuss tasks design and implementation freely, along with the utilization of a structured knowledge pool included in a TMS. A K-OL style thus helps hotel establishments to create positive contexts for facilitating task performing by making KM tools and philosophy available and visible, motivating their use in the development of tasks at work (Shamim et al., 2019). Hence, knowledge-oriented leaders are able to stimulate positive innovative behaviors among employees, facilitating the acquisition and application of knowledge (Kim et al., 2021). Additionally, this leadership style encourages goal achievement by providing clear vision and direction on KM goals. It also becomes a guide on how employees should do their work, offering them autonomy to carry out tasks by using KM tools and allowing them the adaptation of tasks to changes occurring while work is being developed (Shamim et al., 2019).

Knowledge diversity in hotel establishments can sometimes generate dysfunctional social interactions, but it can also lead to great benefits if managers play active roles to lead effective teamwork processes through a TMS (Zhang and Guo, 2019). In this sense, communication barriers should first be broken through the development of a TMS. For example, leaders could increase meetings and training frequency, build effective networks or encourage the use of social media to pre-familiarize team members. With the current level of globalization, knowledge-oriented leaders could also optimize the use of technology networks. Hence, they should stimulate cooperation when the diversity of existing knowledge is high (Zhang and Guo, 2019). Nevertheless, in teams with highly homogeneous knowledge, leaders should encourage training and specialization through exploratory learning and knowledge sharing with other members of the hotel establishment. Alternatively, in heterogeneous teams, knowledge-oriented leaders should motivate employees to improve trust and collaboration with members of other functional units or departments (Guo et al., 2019; Zhang and Guo, 2019). In addition, knowledge-oriented leaders can act as “teachers” to help company members to recognize knowledge boundaries, reconcile cognitive conflicts, perceive benefits of learning and encourage them to learn proactively. Moreover, they should try to develop a climate of psychological and motivational safety through their influence and power to mitigate unhealthy motivations for not sharing, or even “hiding,” knowledge.

Finally, hotel establishments could improve services quality by promoting employees’ learning about customer preferences and sharing them through internal networks (Hussain et al., 2016). Through positive knowledge sharing behaviors and the organization and structuring of knowledge by means of a highly developed TMS, hotel establishments can use their available resources to improve processes of service delivery, innovation behavior and performance.

6.3 Limitations and directions for future research

This study is not free of limitations. Thus, the research has a cross-sectional design, so causal effects are difficult to be observed, especially for the dependent variable, IC, which need long-term investment in resource and routines integration and accumulation over time. Longitudinal studies covering longer periods of time could be developed to examine long-term effects of TMC on innovation and TMS investments and their consequences on competitive advantages of hotel establishments. Moreover, this paper has not established specific connections between K-OL and each of the TMS dimensions, as well as between each of the TMS dimensions and IC. Due to the lack of studies that have analyzed the relationship between K-OL and TMS, we have rather focused on a generic connection, so the research has an exploratory rather than confirmatory purpose. The analysis of these specific relationships remains in the agenda for future research.

Furthermore, it is likely that common variance bias can still be a concern for this study. To check for this issue, we calculated ICCs for the most relevant variables of the study, which showed acceptable values, and a post-hoc assessment through a Harman’s test, also showing not biases. In any case, the number of multiple respondents (one or more per hotel) was not very high, so we must be cautious about this research design issue and its results. In addition, the sample of inland hotels was not very large, so a study extending the number of hotel establishments would help us to validate the results of the study. For example, we could widen the scope of the research by considering other kind of establishments (coast hotels) or even by including inland hotels from other European countries having similar customer demands. Moreover, widening the sample would be useful to check model heterogeneity by segmentation (for example, by means of the FIMIX algorithm), as heterogeneity is a potential problem that may affect the unobserved structure of the latent constructs and so, the established relationships in the model (Hair et al., 2017).

In addition, this paper has treated both task and process conflict as a single construct (TMC). Although we have considered conceptual aspects to add process and task conflict into one construct and rigorous techniques have been applied to corroborate this grouping of items (explorative factor analysis), we could analyze in future papers the interrelationships of each type of conflict with TMS or even with TMS dimensions (specialization, coordination, credibility) to enrich our findings and theoretical implications of this research.

Finally, this paper has generally assumed a perspective of KM toward conflict mitigation based on human resource management rather than technological solutions, and there are also new KM emerging topics based on digital technology that can help firms to solve problems, anticipate conflicts based on task management at work and deal with psychosociological issues of their human resources. They can also contribute to establish a richer context to manage conflict and develop IC. For example, the creation of immersive work environments in the metaverse (virtual environments) and the use of data visualization tools and behavioral analytics (Zvarikova et al., 2022), along with other instruments such as augmented analytics and virtual connectivity tools, predictive modeling and digital twin technologies (Michalikova et al., 2022) can allow companies to anticipate dysfunctional behaviors, and also to develop a more precise design of work task and activities to prevent excessive conflict, avoiding unwanted company results. The consideration of these technological-based factors along with more “traditional” KM tools and philosophy offer, from a theoretical and practical points of view, possibilities for building a further integrative tool “box” through which firms may improve their IC by means of TMC mitigation.


This research has been financially supported by Junta de Comunidades de Castilla-La Mancha and the European Regional Development Fund (ERDF) of the EU (Grant number: SBPLY/21/180501/000260).

Miguel González-Mohíno is currently working at the University of Córdoba by means of a Margarita Salas Grant (a Spanish Fellowship for the training of young doctors), obtained at the University of Castilla-La Mancha in 2021.


Research model

Figure 1

Research model

Structural model

Figure 2

Structural model

Research information

Demographics Three, four and five-star hotel establishments in inland Spain (total – 767 hotel establishments)
Geographical scope Spain inland provinces
Sample size 118 hotel establishments
Target Employees with a responsibility position on a team or group, such as reception services managers, human resource managers or administration managers
Data collection method Online survey, phone contact
Response rate 15.38% (118 out of 767)
Sample error ± 8.3% (p = q = 50%; the most unfavorable case)
Confidence level 95%
Fieldwork completion date December 2017 – October 2018
Type of sampling Convenience

Source: The authors

Hotel establishments profile

Variable Category No. %
Years operating 1–5 Years 16 13.56
6–10 years 15 12.71
11–15 Years 29 24.58
16–20 Years 10 8.47
More than 20 Years 48 40.68
Number of employees 1–5 4 3.39
6–10 17 14.41
11–15 19 16.10
16–20 16 13.56
More than 20 61 52.55
Property Independent 62 52.54
Belonging to a hotel chain 56 47.45
Category (number of stars) 3 stars 36 30.51
4 stars 68 57.63
5 stars 14 11.86
Capacity (number of rooms) Kid-friendly (up to 100 vacancies) 60 50.85
Small (from 101 to 150 vacancies) 29 24.58
Medium (from 151 to 300 vacancies) 19 16.10
Large (more than 300 vacancies) 10 8.47

Source: The authors

Construct indicators (reflective measures) and measurement model

Construct Indicators Loadings λ Cronbach’s α Rho_A Composite reliability (IFC) AVE
Knowledge Oriented Leadership
0.848 0.925 0.886 0.612
Task Management Conflict (TMC) TMC1
0.918 0.956 0.935 0.705
Innovation capabilities (IC) IC1
0.932 0.960 0.938 0.580

*K-O-L4 was removed from the final model

Source: The authors

Discriminant validity: correlations, Fornell–Larcker criterion and Heterotrait–Monotrait (HTMT)

TMC Quadratic effect IC K-OL TMS Size
TMC 0.840 0.709 0.260 0.311 0.050
Quadratic effect (TCM-IC) 0.686** 1 0.105 0.124 0.046
IC −0.315** −0.041 0.762 0.719 0.169
K-OL −0.331** −0.084 0.664** 0.782 0.047
Transactive Memory Systems (TMS) −0.410** −0.057 0.541** 0.611** 0.691
Size 0.043 0.046 0.157* 0.020 −0.022 1

Diagonal: Discriminant validity with the Fornell–Larcker criterion; Below the diagonal: correlations between constructs and level of significance;


p <0.01 and


p <0.05); Above the diagonal: HTMT values; TMS is considered a formative measure (second order), with HTMT values always scoring 1

Source: The authors

Formative construct: variance inflation factors and weights

Variable Dimension Variance inflation factor (VIF) Weights T-value P value
TMS Coordination 1.844 0.393*** 16.057 0.000
Credibility 1.710 0.381*** 13.863 0.000
Specialization 1.582 0.414*** 13.103 0.000

Source: The authors

Structural paths: direct and indirect relationships

Relationship Path coefficient (β) T-value (bootstrapping) P value Hypothesis support
TMC – IC (Quadratic effect) 0.152 1.824 0.068 H1 not supported
TMS – TMC (Direct effect) −0.332* 2.446 0.014 H2 supported
KOL – TMS (Direct effect) 0.611* 10.487 0.000 H3 supported
KOL – TMC (Direct effect) −0.128 1.273 0.203 H4 not supported
KOL – TMS – TMC (Mediating effect) −0.330* 3.711 0.000 H5 supported
TMS – TMC – IC (Indirect effect) 0.181* 2.297 0.022 H6 supported
KOL – TMS – TMC – IC (Specific indirect effects) 0.111* 2.133 0.033 H7 supported

*Significant with p < 0.05 (one-tailed test)

Source: The authors

Model’s predictive relevance

Construct R2 P values Q² (= 1-SSE/SSO)
TMC 0.179* 0.048 0.110
TMS 0.373* 0.002 0.258
IC 0.185* 0.000 0.069

Significant with p < 0.05

Source: The authors



The weights of the three dimensions are obtained from the first stage of the analysis in PLS. This means that the coefficient of determination (R2) of the TMS at this stage is 1, and so this construct is perfectly explained by its three dimensions. The calculation that provides the value for TMS dimensions is determined in the first stage of the analysis, by extracting the scores of the latent variables of specialization, coordination and credibility by means of the PLS algorithm, and subsequently they are included as new indicators to analyze them in a global model in a second stage, with an R2 = 0.373.

Appendix. Study variables

Knowledge-oriented leadership (K-OL)

K-OL1: The management style implemented in the hotel establishment has created an environment for responsible behavior, teamwork and knowledge sharing.

K-OL2: Managers in the hotel establishment assume the role of knowledge leaders, which is mainly characterized by promoting open ideas, tolerance of mistakes and mediation for the company’s objectives achievement.

K-OL3: The management style implemented in the hotel establishment is characterized by promoting learning from experience and tolerance to mistakes (up to a certain point).

K-OL4: Managers work as knowledge advisors, and controls are only an assessment of the achievement of objectives and goals.

K-OL5: The management style implemented in the hotel establishment promotes the acquisition of external knowledge and communication between employees.

K-OL6: Managers of the hotel establishment reward employees who share and apply their knowledge.

Transactive memory systems (TMS). Specialization – SPE; Credibility – CRED; Coordination – COOR

TMS1(SPE): Every hotel employee has specialized knowledge about specific aspects of work tasks.

TMS2(SPE): Hotel employees have knowledge about specific work tasks that other hotel members do not possess.

TMS3(SPE): Every hotel employee has unique experience in specific areas of activity.

TMS4(SPE): The specialized knowledge of specific employees is necessary to achieve the hotel’s goals and objectives.

TMS5(SPE): Every hotel employee is aware of what expertise other hotel employees have in specific areas.

TMS6(CRED): Hotel employees feel comfortable in accepting suggestions from other hotel members.

TMS7(CRED): Hotel employees trust the knowledge and opinions of other members, considering them credible.

TMS8(CRED): Hotel employees frequently trust the information that other hotel members bring to discussions about tasks and activities.

TMS9(CRED): When information is provided by hotel members, this is frequently re-checked (reversed item).

TMS10(CRED): Employees do not trust other hotel members due to their lack of experience or skills (reversed item).

TMS11(COOR): The hotel establishment works in a well-coordinated manner.

TMS12(COOR): Few misunderstandings arise in the hotel establishment about what and how to develop tasks and activities at work.

TMS13(COOR): Hotel employees have frequently to figure out what work to develop and start every task from scratch (reversed item).

TMS14(COOR): The hotel establishment has developed routines and standards to do tasks and activities smoothly and efficiently.

TMS15(COOR): There are frequent misunderstandings about how to carry out tasks and activities at work (reversed item).

Task management conflict (TMC)

TMC1: The difference of ideas about how to carry out work tasks frequently generates conflicts between colleagues.

TMC2: Duties assigned to tasks development generate frequent disagreements between colleagues.

TMC3: Projects in which employees engaged generate frequents and contradictory discussions regarding their design and the manner they are developed.

TMC4: There are frequent disagreements about who should perform specific tasks in workgroups.

TMC5: Responsibilities assigned to employees about work tasks frequently generate arguments and confrontations between employees.

TMC6: The allocation of resources (materials, information, tools, etc.) among the members of the working groups generates frequent disagreements between colleagues.

Innovation capabilities (IC)

IC1: In the last year, the hotel establishment has introduced a very significant number of new services.

IC2: In the last year, the hotel establishment has introduced a very significant number of improvements in the existing services offered.

IC3: In the last year, the hotel establishment has introduced more services (new or improved) than its main competitors.

IC4: In the last year, the hotel establishment has introduced more services (new or improved) than the industry average.

IC5: In the last year, the hotel establishment has introduced more services (new or improved) than a year ago.

IC6: The hotel establishment continually develops new programs to reduce costs.

IC7: The hotel establishment has valuable knowledge to innovate in technological processes.

IC8: The hotel establishment has valuable knowledge about the development of new systems for the organization of work.

IC9: The hotel establishment has developed new ways of organizing its services more efficiently in the last year.

IC10: The hotel establishment has offered services through new sustainable processes during the last year.

IC11: The hotel establishment manages the organization of services more efficiently than a year ago by having introduced new technological processes into business.


Afzalur Rahim, M. (2002), “Toward a theory of managing organizational conflict”, International Journal of Conflict Management, Vol. 13 No. 3, pp. 206-35.

Alavi, M. and Leidner, D.E. (2001), “Review: knowledge management and knowledge management systems: conceptual foundations and research issues”, MIS Quarterly, Vol. 25 No. 1, p. 107.

Ali, A., Wang, H. and Khan, A.N. (2019), “Mechanism to enhance team creative performance through social media: a transactive memory system approach”, Computers in Human Behavior, Vol. 91, pp. 115-26.

Anderson, N., De Dreu, C.K. and Nijstad, B.A. (2004), “The routinization of innovation research: a constructively critical review of the state‐of‐the‐science”, Journal of Organizational Behavior, Vol. 25 No. 2, pp. 147-73.

Argote, L. and Ingram, P. (2000), “Knowledge transfer: a basis for competitive advantage in firms”, Organizational Behavior and Human Decision Processes, Vol. 82 No. 1, pp. 150-69.

Babalola, M.T., Stouten, J., Euwema, M.C. and Ovadje, F. (2018), “The relation between ethical leadership and workplace conflicts: the mediating role of employee resolution efficacy”, Journal of Management, Vol. 44 No. 5, pp. 2037-63.

Bachrach, D.G., Lewis, K., Kim, Y., Patel, P.C., Campion, M.C. and Thatcher, S.M.B. (2019), “Transactive memory systems in context: a meta-analytic examination of contextual factors in transactive memory systems development and team performance”, Journal of Applied Psychology, Vol. 104 No. 3, pp. 464-93.

Badrinarayanan, V., Madhavaram, S. and Granot, E. (2011), “Global virtual sales teams (GVSTs): a conceptual framework of the influence of intellectual and social capital on effectiveness”, Journal of Personal Selling & Sales Management, Vol. 31 No. 3, pp. 311-24.

Bai, Y., Lin, L. and Li, P.P. (2016), “How to enable employee creativity in a team context: a cross-level mediating process of transformational leadership”, Journal of Business Research, Vol. 69 No. 9, pp. 3240-50.

Basco, R., Hair, J.F., Jr, Ringle, C.M. and Sarstedt, M. (2022), “Advancing family business research through modeling nonlinear relationships: comparing PLS-SEM and multiple regression”, Journal of Family Business Strategy, Vol. 13 No. 3, p. 100457.

Bass, B.M. and Avolio, B.J. (1996), “Multifactor leadership questionnaire”, Western Journal of Nursing Research.

Bass, B.M. and Avolio, B.J. (2000), Manual for the Multifactor Leadership Questionnaire (Form 5X), Mindgarden, Redwood City, CA.

Becker, J.-M., Proksch, D. and Ringle, C.M. (2022), “Revisiting gaussian copulas to handle endogenous regressors”, Journal of the Academy of Marketing Science, Vol. 50 No. 1, pp. 46-66.

Bessant, J., Lamming, R., Noke, H. and Phillips, W. (2005), “Managing innovation beyond the steady state”, Technovation, Vol. 25 No. 12, pp. 1366-76.

Bibi, G., Padhi, M. and Dash, S.S. (2021), “Theoretical necessity for rethinking knowledge in knowledge management literature”, Knowledge Management Research & Practice, Vol. 19 No. 3, pp. 396-407.

Bryant, S.E. (2003), “The role of transformational and transactional leadership in creating, sharing and exploiting organizational knowledge”, Journal of Leadership & Organizational Studies, Vol. 9 No. 4, pp. 32-44.

Cabeza-Pullés, D., Gutierrez-Gutierrez, L.J. and Llorens-Montes, F.J. (2018), “Drivers for performance in innovative research groups: the mediating role of transactive memory system”, BRQ Business Research Quarterly, Vol. 21 No. 3, pp. 180-94.

Cantallops, A.S. and Salvi, F. (2014), “New consumer behavior: a review of research on eWOM and hotels”, International Journal of Hospitality Management, Vol. 36, pp. 41-51.

Chang, M.L. (2017), “On the relationship between intragroup conflict and social capital in teams: a longitudinal investigation in Taiwan”, Journal of Organizational Behavior, Vol. 38 No. 1, pp. 3-27.

Chin, W.W. (1998), “Commentary: issues and opinion on structural equation modeling”, MIS Quarterly, Vol. 22 No. 1, pp. vii-xvi.

Choi, H.J. and Kim, Y.T. (2012), “Work‐family conflict, work‐family facilitation, and job outcomes in the Korean hotel industry”, International Journal of Contemporary Hospitality Management.

Chow, W.S. and Chen, Y. (2012), “Corporate sustainable development: testing a new scale based on the mainland Chinese context”, Journal of Business Ethics, Vol. 105 No. 4, pp. 519-33.

Cooke, F.L., Saini, D.S. and Wang, J. (2014), “Talent management in China and India: a comparison of management perceptions and human resource practices”, Journal of World Business, Vol. 49 No. 2, pp. 225-35.

Currie, D., Gormley, T., Roche, B. and Teague, P. (2017), “The management of workplace conflict: contrasting pathways in the HRM literature”, International Journal of Management Reviews, Vol. 19 No. 4, pp. 492-509.

Damanpour, F. (2010), “An integration of research findings of effects of firm size and market competition on product and process innovations”, British Journal of Management, Vol. 21 No. 4, pp. 996-1010.

Datta, A. and Singh, R. (2018), “Determining the dimensions of organizational climate perceived by the hotel employees”, Journal of Hospitality and Tourism Management, Vol. 36, pp. 40-48.

De Dreu, C.K. (2006), “When too little or too much hurts: evidence for a curvilinear relationship between task conflict and innovation in teams”, Journal of Management, Vol. 32 No. 1, pp. 83-107.

De Dreu, C.K.W. and Weingart, L.R. (2003), “Task versus relationship conflict, team performance, and team member satisfaction: a meta-analysis”, Journal of Applied Psychology, Vol. 88 No. 4, pp. 741-49.

De Dreu, C.K.W., van Dierendonck, D. and Dijkstra, M.T.M. (2004), International Journal of Conflict Management, Vol. 15 No. 1, pp. 6-26.

Diamantopoulos, A. and Winklhofer, H.M. (2001), “Index construction with formative indicators: an alternative to scale development”, Journal of Marketing Research, Vol. 38 No. 2, pp. 269-77.

Donate, M.J. and Guadamillas, F. (2011), “Organizational factors to support knowledge management and innovation”, Journal of Knowledge Management, Vol. 15 No. 6, pp. 890-914.

Donate, M.J. and Guadamillas, F. (2015), “An empirical study on the relationships between knowledge management, knowledge-oriented human resource practices and innovation”, Knowledge Management Research & Practice, Vol. 13 No. 2, pp. 134-48.

Donate, M.J. and Sánchez de Pablo, J.D. (2015), “The role of knowledge-oriented leadership in knowledge management practices and innovation”, Journal of Business Research, Vol. 68 No. 2, pp. 360-70.

Donate, M.J., Pena, I. and Sanchez de Pablo, J.D. (2016), “HRM practices for human and social capital development: effects on innovation capabilities”, The International Journal of Human Resource Management, Vol. 27 No. 9, pp. 928-53.

Donate, M.J., González-Mohíno, M., Appio, F.P. and Bernhard, F. (2022), “Dealing with knowledge hiding to improve innovation capabilities in the hotel industry: the unconventional role of knowledge-oriented leadership”, Journal of Business Research, Vol. 144, pp. 572-86.

Fachrunnisa, O., Adhiatma, A. and Tjahjono, H.K. (2020), “Cognitive collective engagement: relating Knowledge-Based practices and innovation performance”, Journal of the Knowledge Economy, Vol. 11 No. 2, pp. 743-65.

Falk, R.F. and Miller, N.B. (1992), A Primer for Soft Modeling, University of Akron Press, Akron.

Farh, J.-L., Lee, C. and Farh, C.I. (2010), “Task conflict and team creativity: a question of how much and when”, Journal of Applied Psychology, Vol. 95 No. 6, p. 1173.

Fleiss, J.L. (1986), “Analysis of data from multiclinic trials”, Controlled Clinical Trials, Vol. 7 No. 4, pp. 267-75.

Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.

Gagné, M., Tian, A.W., Soo, C., Zhang, B., Ho, K.S.B. and Hosszu, K. (2019), “Different motivations for knowledge sharing and hiding: the role of motivating work design”, Journal of Organizational Behavior, Vol. 40 No. 7, pp. 783-99.

Gefen, D. and Straub, D. (2005), “A practical guide to factorial validity using PLS-Graph: tutorial and annotated example”, Communications of the Association for Information Systems, Vol. 16 No. 1, p. 5.

Giebels, E., de Reuver, R.S., Rispens, S. and Ufkes, E.G. (2016), “The critical roles of task conflict and job autonomy in the relationship between proactive personalities and innovative employee behavior”, The Journal of Applied Behavioral Science, Vol. 52 No. 3, pp. 320-41.

Gino, F., Argote, L., Miron-Spektor, E. and Todorova, G. (2010), “First, get your feet wet: the effects of learning from direct and indirect experience on team creativity”, Organizational Behavior and Human Decision Processes, Vol. 111 No. 2, pp. 102-15.

Grant, R.M. (1996), “Toward a knowledge-based theory of the firm”, Strategic Management Journal, Vol. 17 No. S2, pp. 109-22.

Guo, H., Zhang, L., Huo, X. and Xi, G. (2019), “When and how cognitive conflict benefits cross-functional project team innovation”, International Journal of Conflict Management, Vol. ahead-of-print No. ahead-of-print, pp. 514-37.

Hair, J.F., Sarstedt, M., Hopkins, L. and Kuppelwieser, V.G. (2014), “Partial least squares structural equation modeling (PLS-SEM)”, European Business Review, Vol. 26 No. 2, pp. 106-21.

Hair, J.F., Sarstedt, M., Ringle, C.M. and Gudergan, S.P. (2017), Advanced Issues in Partial Least Squares Structural Equation Modeling, SAGE publications.

Hammedi, W., Van Riel, A.C. and Sasovova, Z. (2013), “Improving screening decision making through transactive memory systems: a field study”, Journal of Product Innovation Management, Vol. 30 No. 2, pp. 316-30.

Hansen, M.T., Mors, M.L. and Løvås, B. (2005), “Knowledge sharing in organizations: multiple networks, multiple phases”, Academy of Management Journal, Vol. 48 No. 5, pp. 776-93.

Heavey, C. and Simsek, Z. (2015), “Transactive memory systems and firm performance: an upper echelons perspective”, Organization Science, Vol. 26 No. 4, pp. 941-59.

Hood, A.C., Bachrach, D.G. and Lewis, K. (2014), “Transactive memory systems, conflict, size and performance in teams”, Journal of Leadership, Accountability & Ethics, Vol. 11 No. 3.

Hülsheger, U.R., Anderson, N. and Salgado, J.F. (2009), “Team-level predictors of innovation at work: a comprehensive meta-analysis spanning three decades of research”, Journal of Applied Psychology, Vol. 94 No. 5, p. 1128.

Hussain, K., Konar, R. and Ali, F. (2016), “Measuring service innovation performance through team culture and knowledge sharing behaviour in hotel services: a PLS approach”, Procedia - Social and Behavioral Sciences, Vol. 224, pp. 35-43.

Jehn, K.A. and Mannix, E.A. (2001), “The dynamic nature of conflict: a longitudinal study of intragroup conflict and group performance”, Academy of Management Journal, Vol. 44 No. 2, pp. 238-51.

Jundt, D.K., Shoss, M.K. and Huang, J.L. (2015), “Individual adaptive performance in organizations: a review”, Journal of Organizational Behaviour, Vol. 36 No. S1, pp. 53-71.

Karatepe, O.M. and Aleshinloye, K.D. (2009), “Emotional dissonance and emotional exhaustion among hotel employees in Nigeria”, International Journal of Hospitality Management, Vol. 28 No. 3, pp. 349-58.

Karatepe, O.M. and Olugbade, O.A. (2009), “The effects of job and personal resources on hotel employees’ work engagement”, International Journal of Hospitality Management, Vol. 28 No. 4, pp. 504-12.

Khan, A.G., Li, Y., Akram, Z. and Akram, U. (2022), “Does bad gossiping trigger for targets to hide knowledge in morally disengaged? New multi-level insights of team relational conflict”, Journal of Knowledge Management, Vol. 26 No. 9, pp. 2370-94.

Khan, N.A., Khan, A.N., Soomro, M.A. and Khan, S.K. (2020), “Transformational leadership and civic virtue behavior: valuing act of thriving and emotional exhaustion in the hotel industry”, Asia Pacific Management Review, Vol. 25 No. 4, pp. 216-25.

Kianto, A. and Andreeva, T. (2014), “Knowledge management practices and results in service‐oriented versus product‐oriented companies”, Knowledge and Process Management, Vol. 21 No. 4, pp. 221-30.

Kim, T.T. and Lee, G. (2013), “Hospitality employee knowledge-sharing behaviors in the relationship between goal orientations and service innovative behavior”, International Journal of Hospitality Management, Vol. 34, pp. 324-37.

Kim, B.P., Murrmann, S.K. and Lee, G. (2009), “Moderating effects of gender and organizational level between role stress and job satisfaction among hotel employees”, International Journal of Hospitality Management, Vol. 28 No. 4, pp. 612-19.

Kim, M., Koo, D.-W. and Han, H.-S. (2021), “Innovative behavior motivations among frontline employees: the mediating role of knowledge management”, International Journal of Hospitality Management, Vol. 99, p. 103062.

Ko, D.W.W., Chen, P.Y., Chen, D.C.-H.S., Wu, D.M.-S.S. and Liu, P.G. (2021), “Proactive environmental strategy, foreign institutional pressures, and internationalization of Chinese SMEs”, Journal of World Business, Vol. 56 No. 6, p. 101247.

Kundapur, P.P. and Rodrigues, L.L. (2012), “Simulating knowledge worker adoption rate of KMS: an organizational perspective”, International Journal of Innovation, Management and Technology, Vol. 3 No. 4, p. 459.

Kuo, N.-T., Chang, K.-C., Chen, M.-C. and Hsu, C.-L. (2012), “Investigating the effect of service quality on customer post-purchasing behaviors in the hotel sector: the moderating role of service convenience”, Journal of Quality Assurance in Hospitality & Tourism, Vol. 13 No. 3, pp. 212-34.

Kwok, L., Xie, K.L. and Richards, T. (2017), “Thematic framework of online review research”, International Journal of Contemporary Hospitality Management, Vol. 29 No. 1, pp. 307-54.

Langfred, C.W. and Moye, N. (2014), “Does conflict help or hinder creativity in teams? An examination of conflict's effects on creative processes and creative outcomes”, International Journal of Business and Management, Vol. 9 No. 6, pp. 30-42.

Lavelle, M., Darzi, A., Starodub, R. and Anderson, J.E. (2022), “The role of transactive memory systems, psychological safety and interpersonal conflict in hospital team performance”, Ergonomics, Vol. 65 No. 3, pp. 519-29.

Lee, J.-C., Wang, Y.-T. and Chen, C.-Y. (2020), “The effect of transactive memory systems on process tailoring in software projects: the moderating role of task conflict and shared temporal cognitions”, Journal of Systems and Software, Vol. 164, p. 110545.

Lewis, K. (2003), “Measuring transactive memory systems in the field: scale development and validation”, Journal of Applied Psychology, Vol. 88 No. 4, pp. 587-604.

Lewis, K. and Herndon, B. (2011), “Transactive memory systems: current issues and future research directions”, Organization Science, Vol. 22 No. 5, pp. 1254-65.

Lian, L.K. and Tui, L.G. (2012), “Leadership styles and organizational citizenship behavior: the mediating effect of subordinates’ competence and downward influence tactics”, Journal of Applied Business and Economics, Vol. 13 No. 2, pp. 59-96.

Lin, J.-H., Wong, J.-Y. and Ho, C-h (2013), “Promoting frontline employees' quality of life: leisure benefit systems and work-to-leisure conflicts”, Tourism Management, Vol. 36, pp. 178-87.

Littlepage, G.E., Hollingshead, A.B., Drake, L.R. and Littlepage, A.M. (2008), “Transactive memory and performance in work groups: specificity, communication, ability differences, and work allocation”, Group Dynamics: Theory, Research, and Practice, Vol. 12 No. 3, pp. 223-41.

Liu, C., Yang, L.-Q. and Nauta, M.M. (2013), “Examining the mediating effect of supervisor conflict on procedural injustice–job strain relations: the function of power distance”, Journal of Occupational Health Psychology, Vol. 18 No. 1, p. 64.

MacKinnon, D.P. (2008), “Introduction to statistical mediation analysis”, Multivariate Applications Series, Taylor & Francis Group/Lawrence Erlbaum Associates, New York, NY.

Madanoglu, M. and Ozdemir, O. (2016), “Is more better? The relationship between meeting space capacity and hotel operating performance”, Tourism Management, Vol. 52, pp. 74-81.

Marques-Quinteiro, P., Curral, L., Passos, A., Lewis, K. and Gomes, C. (2019), “How transactive memory systems and reflexivity relate with innovation in healthcare teams”, Análise Psicológica, Vol. 37 No. 1, pp. 41-51.

Medina, F.J., Munduate, L., Dorado, M.A., Martínez, I. and Guerra, J.M. (2005), “Types of intragroup conflict and affective reactions”, Journal of Managerial Psychology, Vol. 20 Nos 3/4, pp. 219-30.

Mentzas, G.N. (1993), “Coordination of joint tasks in organizational processes”, Journal of Information Technology, Vol. 8 No. 3, pp. 139-50.

Michalikova, K.F., Suler, P. and Robinson, R. (2022), “Virtual hiring and training processes in the metaverse: remote work apps, sensory algorithmic devices, and decision intelligence and modeling”, Psychosociological Issues in Human Resource Management, Vol. 10 No. 1, pp. 50-63.

Moreland, R.L. and Myaskovsky, L. (2000), “Exploring the performance benefits of group training: transactive memory or improved communication?”, Organizational Behavior and Human Decision Processes, Vol. 82 No. 1, pp. 117-33.

Muñoz, R.M., Andrade, S.M., Peña, I. and Donate, M.J. (2023), “Wellness programs in times of COVID-19, perceived organizational support and affective commitment: effects on employee innovative behavior”, European Journal of Innovation Management, Vol. 26 No. 7, pp. 23-44.

Naqshbandi, M.M. and Jasimuddin, S.M. (2018), “Knowledge-oriented leadership and open innovation: role of knowledge management capability in France-based multinationals”, International Business Review, Vol. 27 No. 3, pp. 701-13.

Nicolau, J.L., Mellinas, J.P. and Martín-Fuentes, E. (2020), “Satisfaction measures with monetary and non-monetary components: hotel’s overall scores”, International Journal of Hospitality Management, Vol. 87, p. 102497.

Nieves, J., Quintana, A. and Osorio, J. (2014), “Knowledge-based resources and innovation in the hotel industry”, International Journal of Hospitality Management, Vol. 38, pp. 65-73.

Nitzl, C., Roldan, J.L. and Cepeda, G. (2016), “Mediation analysis in partial least squares path modeling: helping researchers discuss more sophisticated models”, Industrial Management & Data Systems, Vol. 116 No. 9.

Nonaka, I. and Takeuchi, H. (1995), The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford University Press, New York, NY.

Ohly, S., Sonnentag, S. and Pluntke, F. (2006), “Routinization, work characteristics and their relationships with creative and proactive behaviors”, Journal of Organizational Behavior, Vol. 27 No. 3, pp. 257-79.

Parayitam, S., Usman, S.A., Namasivaayam, R.R. and Naina, M.S. (2021), “Knowledge management and emotional exhaustion as moderators in the relationship between role conflict and organizational performance: evidence from India”, Journal of Knowledge Management, Vol. 25 No. 6, pp. 1456-85.

Peltokorpi, V. and Hasu, M. (2016), “Transactive memory systems in research team innovation: a moderated mediation analysis”, Journal of Engineering and Technology Management, Vol. 39, pp. 1-12.

Peltokorpi, V. and Hood, A.C. (2019), “Communication in theory and research on transactive memory systems: a literature review”, Topics in Cognitive Science, Vol. 11 No. 4, pp. 644-67.

Perry-Smith, J.E. (2006), “Social yet creative: the role of social relationships in facilitating individual creativity”, Academy of Management Journal, Vol. 49 No. 1, pp. 85-101.

Petrou, P., Bakker, A.B. and Bezemer, K. (2019), “Creativity under task conflict: the role of proactively increasing job resources”, Journal of Occupational and Organizational Psychology, Vol. 92 No. 2, pp. 305-29.

Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in organizational research: problems and prospects”, Journal of Management, Vol. 12 No. 4, pp. 531-44.

Porter, M.E. (1985), “Technology and competitive advantage”, Journal of Business Strategy, Vol. 5 No. 3, pp. 60-78.

Rico, R., Sánchez-Manzanares, M., Gil, F. and Gibson, C. (2008), “Team implicit coordination processes: a team knowledge–based approach”, Academy of Management Review, Vol. 33 No. 1, pp. 163-84.

Ringle, C.M., Wende, S. and Becker, J.-M. (2022), SmartPLS 4.0, SmartPLS GmbH, Oststeinbek, available at:

Roberts, T. (2005), “Coaching managers through their conflicts”, Management Services, Vol. 49 No. 4, pp. 16-18.

Salas-Vallina, A., Pasamar, S. and Donate, M.J. (2021), “Well-being in times of ill-being: how AMO HRM practices improve organizational citizenship behaviour through work-related well-being and service leadership”, Employee Relations: The International Journal, Vol. 43 No. 4, pp. 911-35.

Shamim, S., Cang, S. and Yu, H. (2019), “Impact of knowledge oriented leadership on knowledge management behaviour through employee work attitudes”, The International Journal of Human Resource Management, Vol. 30 No. 16, pp. 2387-417.

Shaw, J.D., Zhu, J., Duffy, M.K., Scott, K.L., Shih, H.-A. and Susanto, E. (2011), “A contingency model of conflict and team effectiveness”, Journal of Applied Psychology, Vol. 96 No. 2, pp. 391-400.

Shrout, P.E. and Fleiss, J.L. (1979), “Intraclass correlations: uses in assessing rater reliability”, Psychological Bulletin, Vol. 86 No. 2, pp. 420-28.

Singh, S.K. (2008), “Role of leadership in knowledge management: a study”, Journal of Knowledge Management, Vol. 12 No. 4, pp. 3-15.

Sobel, M.E. (1982), “Asymptotic intervals for indirect effects in structural equations models”, Sociological Methodology, Jossey-Bass, San Francisco, Vol. 13, pp. 290-312.

Somech, A. (2006), “The effects of leadership style and team process on performance and innovation in functionally heterogeneous teams”, Journal of Management, Vol. 32 No. 1, pp. 132-57.

Tajeddini, K. and Trueman, M. (2012), “Managing Swiss hospitality: how cultural antecedents of innovation and customer-oriented value systems can influence performance in the hotel industry”, International Journal of Hospitality Management, Vol. 31 No. 4, pp. 1119-29.

Teece, D.J. (2018), “Business models and dynamic capabilities”, Long Range Planning, Vol. 51 No. 1, pp. 40-49.

Tuominen, M. and Hyvönen, S. (2004), “Organizational innovation capability: a driver for competitive superiority in marketing channels”, The International Review of Retail, Distribution and Consumer Research, Vol. 14 No. 3, pp. 277-93.

Varela, C. and Martín, F. (2011), “Problemas de sostenibilidad del turismo rural en españa”, Anales de Geografía, Vol. 31 No. 1, pp. 171-94.

Wegner, D.M. (1987), “Transactive memory: a contemporary analysis of the group mind”, in Muller, B. and Goethals, G.R. (Eds), Theories of Group Behavior, Springer, New York, NY, pp. 185-208.

Wikhamn, W. (2019), “Innovation, sustainable HRM and customer satisfaction”, International Journal of Hospitality Management, Vol. 76, pp. 102-10.

Wu, G., Liu, C., Zhao, X. and Zuo, J. (2017), “Investigating the relationship between communication-conflict interaction and project success among construction project teams”, International Journal of Project Management, Vol. 35 No. 8, pp. 1466-82.

Yang, L.-R., Huang, C.-F. and Hsu, T.-J. (2014), “Knowledge leadership to improve project and organizational performance”, International Journal of Project Management, Vol. 32 No. 1, pp. 40-53.

Yoon, J.D., Rasinski, K.A. and Curlin, F.A. (2010), “Conflict and emotional exhaustion in obstetrician-gynaecologists: a national survey”, Journal of Medical Ethics, Vol. 36 No. 12, pp. 731-35.

Zhang, L. and Guo, H. (2019), “Enabling knowledge diversity to benefit cross-functional project teams: joint roles of knowledge leadership and transactive memory system”, Information & Management, Vol. 56 No. 8, p. 103156.

Zhang, R., Wang, J. and Hao, J.-X. (2020), “How does knowledge heterogeneity affect transactive memory system in innovation? Evidence from a field study”, Journal of Knowledge Management, Vol. 24 No. 8, pp. 1965-85.

Zhao, X., Mattila, A.S. and Ngan, N.N. (2014), “The impact of frontline employees’ work–family conflict on customer satisfaction: the mediating role of exhaustion and emotional displays”, Cornell Hospitality Quarterly, Vol. 55 No. 4, pp. 422-32.

Zhu, Y., Yang, H. and Bai, G. (2016), “Effect of superior–subordinate intergenerational conflict on job performance of new generation employees”, Social Behavior and Personality: An International Journal, Vol. 44 No. 9, pp. 1499-513.

Zia, N.U. (2020), “Knowledge-oriented leadership, knowledge management behaviour and innovation performance in project-based SMEs. The moderating role of goal orientations”, Journal of Knowledge Management, Vol. 24 No. 8, pp. 1819-39.

Zollo, M. and Winter, S.G. (2002), “Deliberate learning and the evolution of dynamic capabilities”, Organization Science, Vol. 13 No. 3, pp. 339-51.

Zvarikova, K., Cug, J. and Hamilton, S. (2022), “Virtual human resource management in the metaverse: immersive work environments, data visualization tools and algorithms, and behavioral analytics”, Psychosociological Issues in Human Resource Management, Vol. 10 No. 1, pp. 7-20.


Corrigendum: It has come to the attention of the publisher that the article Donate, M.J., Guadamillas, F. and González-Mohíno, M. (2023), “Solving task management conflict in hotel establishments through knowledge management tools: effects on innovation capabilities”, Journal of Knowledge Management, Vol. 27 No. 11, pp. 157-186., contained incorrect funding information. This error was introduced during the submission process. ‘This research has been financially supported by Junta de Comunidades de Castilla-La Mancha (Grant number: SBPLY/21/180501/000260)’ has been changed to ‘This research has been financially supported by Junta de Comunidades de Castilla-La Mancha and the European Regional Development Fund (ERDF) of the EU (Grant number: SBPLY/21/180501/000260).’ The authors sincerely apologise for this error and for any misunderstanding.

Corresponding author

Mario J. Donate can be contacted at:

About the authors

Mario J. Donate is based at the Department of Business Administration, Faculty of Law and Social Sciences, University of Castilla-La Mancha, Ciudad Real, Spain.

Fátima Guadamillas is based at the Department of Business Administration, Faculty of Law and Social Sciences, University of Castilla-La Mancha, Toledo, Spain.

Miguel González-Mohíno is based at the Department of Management, Faculty of Law, Economics and Management, University of Córdoba, Córdoba, Spain.

Related articles