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Research Journal of the Graduate School of Bulacan State University
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A Systematic Literature Review of Shared Leadership
Authors
Francis Nicko B. Domingo*
Graduate School, Bulacan State University, City of Malolos, Bulacan
Gualberto A. Magdaraog Jr.
College of Business Education and Accountancy, Bulacan State University, City of Malolos, Bulacan
*Corresponding Author-Francis Nicko B. Domingo-domingofrancisnicko@gmail.com
Volume 7, Issue No. 2, 2025
Abstract
A Comprehensive and Systematic Review of shared leadership, an increasingly relevant leadership approach in contemporary organizations. Shared Leading is an emergent concept in leadership that brings collective decision-making and accountability distribution within teams or organizations. This review includes a systematic content analysis of existing studies on shared leadership in terms of its theoretical underpinnings, salient features, and general outcomes. As a result, the review scrutinizes results from various academic disciplines and fields, such as organizational behavior, management, and psychology, to understand how shared leadership plays itself across different context and how it affects team performance, innovation, and employee satisfaction. The identification of lacunae in current research efforts can help deepen understanding of the real-world dimensions of shared leadership and pave the way toward enhancing collaborative work environments. Besides, the review discusses measurement issues concerning shared leadership and suggests potential research as well as future research questions on shared leadership mechanisms, antecedents, and consequences.
Keywords: shared leadership, team leadership, leadership, team performance
Introduction
Shared leadership, as an emergent team phenomenon, fundamentally challenges conventional notions of leadership vested in a single individual, instead emphasizing the dispersal of leadership roles and influence among various team members (Zhu et al., 2018). This paradigm shift recognizes the inherent potential within teams to collectively steer themselves toward shared objectives through the synergistic interplay of individual expertise and mutual support (Chiu et al., 2016). The existing literature on shared leadership, despite its progress, has been fragmented with a variety of conceptualizations and operationalizations, leading to limited consensus regarding a suitable overarching theoretical framework and undermining the development of knowledge in this research domain (Zhu et al., 2018).
In other organizations on shared leadership. Understanding leadership functioning in virtual teams becomes critical as organizations increasingly use dispersed teams for talent acquisition (Liao., 2017). The role of shared leadership in improving project success has received increasing interest, yet there is still insufficient understanding of the contextual factors that enable – or prohibit – the emergence of shared leadership within project-based organizations (Abson et., 2023). Knowledge-sharing density emerges as a transformative force, mediating the impact of shared leadership on team innovation. This intricate relationship unveils hidden potential for innovation within construction teams (Soomro et al.,2024). Individual-focused transformational leadership strengthened the positive effect of shared leadership on team members’ average individual creativity, whereas group-focused transformational leadership facilitated the translation of teams with high average individual creativity into teams with high levels of team creativity (He et al., 2020).
Within the evolving domain of organizational science, shared leadership has gained significant traction as a compelling departure from traditional, top-down leadership structures, underscoring the importance of distributed influence and collaborative empowerment in contemporary organizational settings. While the concept of shared leadership has gained considerable attention, the literature still grapples with a lack of definitional clarity, conceptual overlap with other constructs, and methodological complexities in its assessment (Zhu et al., 2018).
To address these challenges and advance the understanding of shared leadership, a comprehensive and systematic review of the literature is needed. Such a review can help to synthesize existing knowledge, identify key themes and debates, highlight gaps in research, and provide directions for future investigations. This review presents the 25 related literature reviews in reputable journals with high impact factors.
Methodology
This systematic literature review adheres to the PRISMA guidelines to ensure methodological rigor and transparency in the synthesis of extant literature on shared leadership. This approach, commonly employed in various research disciplines, including social sciences and engineering, helps minimize biases by meticulously identifying and appraising all relevant literature related to a specific research question (Bolaños et al., 2024). This includes a comprehensive search strategy, rigorous inclusion and exclusion criteria, and a systematic process for data extraction and synthesis, thereby enhancing the reproducibility and validity of the review's findings (Okoli, 2015). The selection of articles for in-depth analysis followed a similar stringent protocol, ensuring that only highly relevant and methodologically sound studies were included, particularly those identified through robust database searches such as Scopus (Bajpai et al., 2024). This comprehensive strategy ensures the inclusion of a diverse range of perspectives and empirical evidence, thereby strengthening the foundation for a nuanced understanding of shared leadership dynamics (Shaheen et al., 2023). This review thoroughly examined 25 literature reviews, focusing on journal impact factor, sampled articles, type/source of data, geographical settings, statistical treatment, and variables used in measuring shared leadership.
Results and Discussion
This section provides the foundation of data sources, geographical locations, statistical analysis used, geographical location of chosen studies, the variable use for shared leadership, its parameters used by the previous researchers, and the concepts or other variables being compared to it. Through this, review was able to distinctly classify and analyze the evolution utilized from year 2014 to current time of shared leadership
Table 1 presents the impact factors of the journals used in the study. The Selected articles were published in the reputable journals in business: Journal of Organizational Behavior, Journal of Applied Psychology, Human Resource Management Review, International Journal of Project Management, Journal of Business Research, Group & Organization Management, Journal of Innovation & Knowledge, Journal of Leadership & Organizational Studies, Leadership & Organization Development Journal, Leadership Quarterly, International Journal of Management Reviews, Personnel Review, Journal of Organizational Behavior Management, Personnel Psychology, Journal of Management and Journal of Leadership & Organizational Studies. The topic regarding Shared Leadership is considered new as most of the studies conducted in relation to it were ranging from 2014 onwards. With these sixteen (16) journals were used in this review from the period of ten (10) years. This is also the reason why the paper only consists of twenty-five (25) related literature and studies due to the limitation of finished studies and that other studies published in journals do not have a score for impact factor. The keywords that were used to look for studies were "shared leadership", and "collective leadership". The latter keywords were used to look for more studies since the chosen topic is not a conventional topic therefore only few were available.
Table 2 shows the review of related literature for the following years is shown in this table and categorized as follows: 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, and 2025. Broader year of review needed to look for more studies since the chosen topic is not a conventional topic therefore only few were available. In addition, other research lacks an impact factor score since they were not published in reputable journals. The year that each reviewed piece of literature was published is also based on this table.
Type of Data
Data in research is vital as it shapes the way that data can be gathered, interpreted, and analyzed. It directs all stages if research from designing, data gathering and data analysis to the interpretation and report. Knowing what type of data guarantees that one applies the proper methods, generating reliable, credible and substantial results. Type of data, it may primary or secondary. Primary are those who garnered interview or survey questionnaire, while in Secondary they’re those who requests data from company or organization this was also who have larger sample size. In the graph shown above six (6) of them were using primary data. On the other hand, nineteen (19) were using secondary data.
Source of Data
The data source in research in very imperative since it has a direct bearing on the validity, credibility, reliability and accuracy of the research findings. It is also essential to ensure that research yields accurate, valid and ethical outcomes. It has an influence on the quality, credibility and applicability of the research findings. Researchers should evaluate and select data sources with caution to improve the credibility and effect of their research. Mostly of the literature review shown above uses secondary as their type of source of data. The following authors uses that are Chiu et al., 2016; Nathapon Siangchokyoo and Ryan L. Kliner 2021; Soomro et al., 2024; Drescher et al., 2014; Fausing et al., 2015; Nicolaides et al., 2014; Sweeney et al., 2019; Scott-Young et al., 2019; Kain Klasmeier and Jens Rowold 2020; He et al., 2020; Ali et al., 2020; Ziegert et al., 2021; Gesche Drescher and Yvonne Garbers 2016; Michael R. Kukenberger and Lauren D'Innocenzo 2019; Gu et al., 2022; D’Innocenzo et al., 2016; Wang et al., 2014; Wu et al., 2018; Friedrich et al., 2016. Meanwhile the other authors uses primary as their type of source of data, these are the following authors, Zhu et al., 2018; Chenwei Liao 2017; Abson et al., 2023; Voordeckers et al., 2025; Kristin L. Cullen-Lester and Francis J. Yammarino 2016; Khumalo et al., 2022.
Sample Size
Sample size is an essential factor in establishing the validity, reliability, and generalizability of research outcomes. A well selected sample size ensures that the study possesses enough power to pick up significant effects, minimizes errors, and makes accurate estimates that can be safely projected back to the larger population. The researcher must meticulously evaluate the sample during the planning stage of the study to balance between statistical soundness and practical considerations. In this systematic literature review the largest sample size conducted by the researcher through primary type of data are Abson et al., 2023 who conducted 34 interviewers. While the largest sample size conducted through secondary type of date are Wang et al., 2014 with 3,439 teams.
Observation
The year of observation in research indicate the time period over which data are collected or observed. The span of the observation period is a vital consideration in research design because it can affect the validity and reliability of the results considerably. It is also crucial in research in order to fully understand phenomena that change over time. The longer the period of observation, the greater the better chance the research will detect long-term impacts, discern cause and effect relationships and uncover significant trends. Short studies are adequate for making short term, particular observations, but longer studies gain insight into the functioning of complicated systems and guarantee the reliability, validity and generalizability of the results. As shown above the longer year of observation are Zhu et al., 2018 with 93 years observation. Next are Khumalo et al., 2022 with 39 years observation, Sweeney et al., 2019 with 23 years observation, Scott-Young et al., 2019 with 17years observation, Wu et al., 2018 with 10 years observation, followed by Michael R. Kukenberger and Lauren D'Innocenzo 2019 with 7 years observation. The rest has almost the same of 1 to 2 years of observation.
Table 4 exhibits the Geographical Settings of Selected Articles. The common countries research related to shared leadership are in Europe, Asia, North America, and Africa. Mostly of the research did not mention their geographical settings. What is the importance of this. The significance of geographical contexts in research is high since it can determine the design of the study, data collection and findings. It is also important in research since it has a direct impact on the relevance, accuracy and relevance of findings. It assists in giving context, explaining local variations and shaping the methodology and findings of research. No matter the subject area – social behavior, health condition, environmental dynamics, economic trends. Appreciation for the geographical dimension guarantees that the research is contextually relevant, context specific and ethical.
Table 5 presents Statistical treatment of sampled articles. Descriptive Analysis and Correlation Analysis are the top most used statistical treatments of the researchers. Descriptive Analysis used by the following researchers Chiu et al., 2016; Soomro et al., 2024; Ziegert et al., 2021; Gesche Drescher and Yvonne Garbers 2016; and Michael R. Kukenberger and Lauren D'Innocenzo 2019. Correlation Analysis used by the following researchers Chenwei Liao 2017, Drescher et al., 2014; D’Innocenzo et al., 2016; Wang et al., 2014; and Wu et al., 2018. Next is Regression Analysis, these are the researchers who used regression analysis, Zhu et al., 2018; He et al., 2020; Gu et al., 2022; Friedrich et al., 2016. These are the researchers who used Statistical Analysis Nathapon Siangchokyoo and Ryan L. Klinger 2021 and Khumalo et al., 2022. These are the researchers who used Network Analysis Ali et al., 2020; Kristin L. Cullen-Lester and Francis J. Yammarino 2016. The rest are using different statistical treatments such as follows. Confirmatory Factor Analysis, Fausing et al., 2015. Moderation Analysis, Nicolaides et al., 2014. Comparative Analysis, Sweeney et al., 2019. Content Analysis, Scott-Young et al., 2019. Bayesian Structural Equation, Kain Klasmeier and Jens Rowold 2020. Qualitative Data Analysis, Abson et al., 2023. Causal Mediation Analysis, Voordeckers et al., 2025. Statistical treatment is important in research because it guarantees accuracy, reliability and validity of the findings and facilitates informed, data-based decisions. Statistical treatment enables researchers to systematically analyze and interpret intricate data, detect significant patterns, test hypotheses and guarantee that conclusions are scientifically valid and relevance. Simply put statistical treatment is the foundation of objective, credible and insightful research in all fields
Variable Usage. All of us know that variable is something you try to measure it may be a phenomenon, a person or a thing. This is to determine the variable usage of shared leadership in each review of literature presented to this study to better understand and to have a clear systematic literature review about shared leadership. Mostly of the researchers used shared leadership as their Independent Variable like Zhu et al., 2018; Chenwei Liao 2017; Soomro et al., 2024; Drescher et al., 2014; Nicolaides et al., 2014; Sweeney et al., 2019; He et al., 2020; Ziegert et al., 2021; Gesche Drescher and Yvonne Garbers 2016; Kristin L. Cullen-Lester and Francis J. Yammarino 2016; Khumalo et al., 2022; D’Innocenzo et al., 2016; Wang et al., 2014; Wu et al., 2018; Friedrich et al., 2016. Some may use it as their moderating variable like, Chiu et al., 2016; Voordeckers et al., 2025; Nathapon Siangchokyoo and Ryan L. Klinger 2021; Fausing et al., 2015; Scott-Young et al., 2019; Kain Klasmeier and Jens Rowold 2020; Ali et al., 2020; Michael R. Kukenberger and Lauren D'Innocenzo 2019; Gu et al., 2022. Variable assist in converting abstract concepts into quantifiable ideas, test hypotheses, and reveal relationships among factors. They are at the heart of study design, statistical analysis and results interpretation. Proper utilization of variables guarantees the validity, reliability, and generalizability of research outcomes, ultimately contributing to knowledge development across disciplines.
Parameters. The parameters are responsible for ensuring the validity, reliability and clarity of the research process and its results. They direct the measurement and interpretation of variables, which is central to making meaningful and accurate conclusions. Parameters usage of shared leadership have gained traction in organizational studies, highlighting its potential to enhance team performance and adaptability (Chiu et al., 2016; Zhu et al., 2018). However, the understanding of its formation, effective implementation, and underlying mechanisms remain limited, calling for more research and analysis (Chiu et al., 2016; Zhu et al., 2018)
Dependent Variables. As we go through in the Dependent Variables, all of the articles use different Dependent Variable in their respective research. But most of them use Performance as their Dependent Variable. Authors who use this as their Dependent Variable are Zhu et al., 2018; Chiu et al., 2016; Voordeckers et al., 2025; Nathapon Siangchokyoo and Ryan L. Klinger 2021; Drescher et al., 2014; Fausing et al., 2015; Nicolaides et al., 2014; Sweeney et al., 2019; Kain Klasmeier and Jens Rowold 2020; Ziegert et al., 2021; Michael R. Kukenberger and Lauren D'Innocenzo 2019; Gu et al., 2022; Kristin L. Cullen-Lester and Francis J. Yammarino 2016; D’Innocenzo et al., 2016; Wu et al., 2018; Friedrich et al., 2016. While others use Effectiveness and Creativity. Authors who use effectiveness as their dependent variable are Chenwei Liao 2017 and Wang et al., 2014. Creativity is the dependent variable of the following authors; He et al., 2020 and Ali et al., 2020. But some articles examine different dependent variables, such as: Team Innovation, Soomro et al., 2024. Predicted Satisfaction, Gesche Drescher and Yvonne Garbers, 2016. Collective Action, Khumalo et al., 2022 and Collective Leadership behaviors, Friedrich et al., 2016.
Discussion
For further discussion about shared leadership, it is important to clarify its definition, distinguish it from similar concepts, tackle measurement problems, and create a comprehensive framework outlining its causes, effects, and limitations (Zhu et al., 2018). It is defined as a dynamic, interactive influence process among individuals in groups, with the aim of leading one another toward the achievement of group or organizational goals (Chiu et al., 2016). Shared leadership transcends conventional hierarchical frameworks, fostering a collaborative environment where influence is distributed among team members. This perspective marks a significant departure from conventional "great man" theories of leadership, which prioritize the traits and capabilities of individual leaders as determinants of success (Zhu et al., 2018). Shared leadership is seen as an internal and informal type of leadership in which numerous team members have an impact on the team and on each other in ways that make task completion easier (Chiu et al., 2016). The degree to which specific elements are effectively shared among team members has a profound impact on overall team effectiveness, underscoring the necessity of a nuanced understanding of shared leadership to maximize team performance and achieve desired outcomes (Chiu et al., 2016; Zhu et al., 2018). The evolution of organizational structures has brought shared leadership to the forefront as a compelling alternative to traditional hierarchical models, particularly in complex and dynamic environments. Traditional leadership theories often concentrate on the attributes and actions of individual leaders, while shared leadership emphasizes the distribution of influence and responsibility among team members, fostering a more collaborative and adaptive approach (Zhu et al., 2018).
To fully understand the complexities of shared leadership, more research is required to address its subtleties, which will result in more effective team dynamics and better organizational results (Chiu et al., 2016; Zhu et al., 2018). A comprehensive review of shared leadership literature is essential to address these issues, providing a clear definition of shared leadership, distinguishing it from similar constructs, tackling measurement challenges, and creating an integrated framework for analysis (Zhu et al., 2018). Future research should focus on exploring new avenues and possibilities within the realm of shared leadership, so that its potential can be fully realized and its effects on organizational dynamics can be maximized (Chiu et al., 2016; Zhu et al., 2018).
Conclusion and Recommendation
Firstly, “shared leadership” has been coming into more focus in comparison to the conventional centralized leadership. It encourages collaboration, collective decision making, and empowerment among members of the team. This method helps organizations to harness different skills, opinions, and experiences, leading to greater creativity and enhanced performance. In addition, the review indicated that shared leadership works best in situations that are fast-paced and multifaceted, as long as there is a willingness to adapt, communicate, and trust one another. The health care and education sectors as well as the information technology industry have utilized this strategy with great success, which shows its applicability across industries.
Nonetheless, the review also found challenges related to the practice of shared leadership, including ambiguity in role assignment, conflict potential, and lack of constant coordination among disparate teams. Moreover, there is a gap in the empirical literature about specific contextual factors that influence the effective use of shared leadership, including culture, team makeup, and external standards.
To summarize, although shared leadership has a great deal of potential benefits, its successful application and implementation requires attention to the design of the organization’s structure, culture, and context within which it is used. Future studies should seek to fill these gaps primarily through ethnographic and experimental studies that track the impact of shared leadership on the productivity of the company over time.
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