research paper organizational leadership

• A-Z Publications

Annual Review of Organizational Psychology and Organizational Behavior

Volume 9, 2022, review article, the science of leadership: a theoretical model and research agenda.

• Andrew M. Carton 1
• View Affiliations Hide Affiliations Affiliations: Management Department, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA; email: [email protected]
• Vol. 9:61-93 (Volume publication date January 2022) https://doi.org/10.1146/annurev-orgpsych-012420-091227
• First published as a Review in Advance on November 10, 2021
• Copyright © 2022 by Annual Reviews. All rights reserved

I review the empirical literature on leadership, focusing on papers published since 2010. To do so, I introduce a framework composed of two features: whether theories ( a ) involve the study of leaders or leading (i.e., the person versus the process) and ( b ) conceptualize leadership as a cause or a consequence (i.e., an independent versus dependent variable). This framework can enable future research to accumulate in a more programmatic fashion and help scholars determine where their own studies are located within the landscape of leadership research. I end the review by critically evaluating existing work, arguing that the most popular subcategory of leadership research—lumped conceptualizations of leading, in which scholars examine multiple leader behaviors within a single construct—has significant limitations and may need to be replaced by a greater focus on split conceptualizations of leading, wherein scholars isolate single leader behaviors.

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Journal of Knowledge Management

ISSN : 1367-3270

Article publication date: 29 May 2020

Issue publication date: 17 June 2020

This paper aims to investigate how the relationships between different leadership approaches and organizational learning have been examined in the literature, from which future research areas can be recommended.

Design/methodology/approach

This systematic literature review applies matrix method to examine major literature in leadership and organizational learning. A total of 57 peer-reviewed English publications from 45 journals were selected and analyzed.

The synthesis of these empirical studies revealed as follows: the relationship between leadership and organizational learning has been mostly quantitatively investigated in many countries and sectors; multiple leadership styles have been identified to ameliorate processes, levels and capabilities of organizational learning and transformational leadership still remains the most commonly used style; there are mediating mechanism and boundary conditions in the relationship between leadership and organizational learning.

Research limitations/implications

The literature search in this study was mainly focused on English articles only; therefore, some papers in other languages may have not been included.

Practical implications

This review offers an overall picture of the existing knowledge of organizational learning and leadership that will be fruitful for practitioners to understand and replicate these concepts.

Originality/value

There are little systematic literature reviews on the relationship between leadership and organizational learning. This paper is among the first systematic reviews to analyze how leadership has been associated with organizational learning and provide potential research directions.

• Organizational learning
• Leadership styles

Do, T.T. and Mai, N.K. (2020), "Review of empirical research on leadership and organizational learning", Journal of Knowledge Management , Vol. 24 No. 5, pp. 1201-1220. https://doi.org/10.1108/JKM-01-2020-0046

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Leadership Models and Work Behavior: An Empirical Analysis of Consequences of Authentic and Transformational Leadership

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• First Online: 20 February 2020

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With increasing importance of organizational effectivity and efficiency measures like Balanced Scorecard and optimization of employee work behavior to achieve higher organizational efficiency, Human Resource activities concerning leadership development and academic leadership research are growing. Throughout the course of the twentieth century, a multitude of empirical studies show primarily positive relationships between different constructs of leadership models and desirable variables of organizational behavior. It becomes apparent, though, that in academic research the selection of analyzed leadership models and their consequences is very heterogeneous. This Master Thesis has the objective to contribute to Leadership Research by applying a comparative empirical study in the–until today–often neglected study population of in-house and sales personnel within the pharmaceutical industry. For this purpose, an online employee survey with N = 137 participants from a leading pharmaceutical company in Germany was conducted. Based on contemporary leadership theory, a range of Hypotheses regarding consequences of modern leadership models is empirically tested. The results of the study reconfirm Identification with Manager, Trust & Loyalty and Employee Satisfaction as consequences of Authentic as well as Transformational leadership. Work context as in-house vs. sales setting shows moderating effects on some of the leadership-consequences relationships. As the research involves multiple structurally different variables as well as constructs and compares feedback of different study populations, tangible management implications to boost desirable work attitudes and behaviors can be derived and appropriately adapted to match the respective work context. Ramifications for future scientific research are also presented.

“The greatest leader is not necessarily the one who does the greatest things. He is the one that gets the people to do the greatest things.” (Comment by Ronald Reagan, former U.S. President)

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Introduction

Leadership and Employees’ Satisfaction in Contemporary Organizations

Leadership Styles, Related Outcomes and Practical Suggestions

1 the importance of leadership for corporate success.

Today’s organizational and business environments become heavily disrupted by challenges stemming from political, economic, social or technological currents and trends. The pharmaceutical industry, for example, faces strains like global, regional or local pressures on product pricing, new Market Access hurdles, compliance guidelines and regulations, competition from innovative, generic or biosimilar companies as well as the advent of digital business models that put corporations under pressure to be effective and efficient. Human Resource (HR) departments evaluate how to best deal with one of the companies’ most important resource: their employees. Therefore, leadership is key in organizations’ strive for long-term success and financial performance. In order to contribute to leadership research and its positive outcomes for organizations’ success, this work’s main objective is to provide an overview of relevant leadership theories, to summarize current scientific literature on consequences of leadership and to empirically test relationships between leadership and defined work attitudes and behaviors. A secondary objective is to close research gaps regarding leadership in different work contexts, esp. with regards to pharmaceutical sales and in-house personnel.

2 The Concept of Leadership

Burns ( 1978 ) stated that “Leadership is one of the most observed, yet least understood, phenomena on earth” (p. 3). This indicates that both the scientific and managerial community operates with various definitions of leadership. Vecchiotti’s ( 2018 ) chronological perspective of leadership definition development starts with a patriarchic view based on characteristics of men situated in positions of authority. Over time, the role of subordinates was recognized and leadership encourages implementers to contribute to achieve mutually agreed goals. A paradigm shift due to new aspects like collaboration, teamwork, work-life balance, continuous feedback and learning becomes apparent (Vecchiotti 2018 ). Consequently, the following definition best reflects the latest view: “Leadership is a long-term, value-based process that encourages leaders and implementers to initiate actions that contribute to achieving a common purpose, and to willingly make significant contributions in meeting mutually agreed to goals.” (Vecchiotti 2011 , p. 6). Leadership, by its processual character, is a construct that has to be considered ambiguous, polymorphic and multifaceted. Von Rostenstiel’s Leadership Model (Fig. 1 ) comprehensively describes the various components and entry points for leadership theory and research (von Rosenstiel 2001 ).

Von Rostenstiel’s Leadership Model. Source: von Rosenstiel ( 2001 )

Von Rosenstiel’s Model is an excellent stimulus to look into four different approaches widely discussed: trait approach, behavioral approach, contingency approach, as well as two contemporary approaches of positive leadership.

Historically, leaders were described by traits (Galton and Eysenck 1869 ). In the 1930s and 1940s, leadership research focused on personal characteristics of an individual and sought to identify personality, social, physical, or intellectual attributes that differentiate leaders from non-leaders. Trait theory was aiming at discovering a built-in set of traits that leaders possess, e.g. “aggressiveness”, “self-control”, “independence”, friendliness”, or “optimism” (Owens 1973 ). A famous example is the “Big 5” Personality Model with the five fundamental dimensions “extraversion”, “agreeableness”, “conscientiousness”, “emotional stability” and “openness to experience” (Costa and McCrae 1992 ; Norman 1963 ; Tupes and Christal 1961 ). Academic research describes “Extraversion” as the most predictive trait of leadership (Bass and Bass 2008 ).

Behavioral theory tries to identify the right things effective leaders do, e.g. how they communicate, motivate, delegate, plan, or handle meetings (Owens 1973 ). The most comprehensive example is the Ohio State Studies with the objective to identify independent dimensions of leadership behavior (Schriesheim and Bird 1979 ). Two key dimensions are “Initiating Structure” and “Consideration”. The former describes task-oriented behavior, e.g. putting high emphasis on work organization, work relationships, deadlines and goal attainment. The latter refers to people-oriented behavior with a focus on mutual trust, respect for subordinates’ ideas, and regard for their feelings (Fleishman and Peters 1962 ). One of the biggest contribution of behavioral theory is the introduction of five leadership styles: (1) the autocratic leader (who permits little or no freedom, relying on his or her position, knowledge or power to reward and punish), (2) the bureaucratic leader (who gives clear orders, relying on the organization’s policies, procedures and rules), (3) the diplomatic leader (who provides limited freedom, relying on personal persuasion), (4) the participative leader (who gives a high degree of freedom and accepts group decisions and majority votes) and (5) the free-reign leader (who lets subordinates operate freely unless asked for invention) (Owens 1973 ).

Contingency approaches of leadership comprise three elements: (1) a dimension of leader behavior (“x”), (2) a criterion by which the effectiveness of the leader may be determined (“y”), (3) an environmental or situational variable (“z”) (Korman 1972 ). The focus is on the environmental or situational impact “z”, which influences the correlation between “x” and “y”. In the 1960s, Fiedler’s Contingency Model is looking for the proper match between a leader’s style (i.e. task- vs. relationship-oriented) and the degree to which the situation gives the leader control. If the right match is achieved, effective group performance follows (Fiedler 1977 ). According to Fiedler’s Model, a situation is assessed in terms of three situational dimensions: (1) leader-member relations, (2) task structure, (3) power situation. The combination of these dimensions leads to eight possible categories of leadership situations (Fiedler 1972 ). Fiedler’s fundamental conclusion is to define two ways to improve leader effectiveness: (1) Change of the leader in order to fit the situation, or (2) Change the situation to fit the leader.

Today, two so-called “positive leadership styles” attract high scholarly and managerial attention: Transformational Leadership (TL) and Authentic Leadership (AL). Transformational leaders motivate and encourage others to outperform expectations (Podsakoff et al. 1990 ). The four components of TL are referred to as the “4 I’s”: Idealized influence/charismatic leadership, Inspirational motivation, Intellectual stimulation, and Individualized consideration. As TL is associated with performance beyond expectations, this model remains at the forefront of scholarly attention (Bass and Reggio 2006 ; Gardner et al. 2010 ; Yaslioglu and Erden 2018 ). At the beginning of the twenty-first century, authentic leadership gained high scholarly attention and is now among the most prominent leadership styles studied (Banks et al. 2016 ; Berkovich 2014 ; Celik et al. 2016 ; Walumbwa et al. 2008 ). Walumbwa et al. ( 2008 ) define AL as a composite of four dimensions: (1) self-awareness (including an understanding of one’s strengths and weaknesses and being cognizant of one’s impact on other people), (2) relational transparency (which means presenting one’s authentic self to others, sharing information and expressing one’s true thoughts and feelings), (3) balanced processing (which means to objectively analyze all relevant data before decision making including challenge deeply held positions), (4) internalized moral perspective (which refers to an integrated form of self-regulation guided by internal moral standards and values versus outside pressures) (Walumbwa et al. 2008 ). In sum, AL is a construct that incorporates traits, behaviors, styles and skills to promote ethical and honest behavior (Covelli and Mason 2017 ).

3 Constructs and Generation of Hypotheses

A recent meta-analytic review by Banks et al. ( 2016 ) indicates construct redundancy of TL and AL, claiming that none of the constructs adds palpable incremental validity beyond the other. Joo and Nimon ( 2014 ) though concluded that both leadership models are complementary, not substitutable (Joo and Nimon 2014 ). Consequently, it is hypothesized that TL and AL both contribute to the relationship of leadership with various dependent variables by explaining incremental variance.

In line with Zaccaro and Klimoski’s ( 2002 ) view that different dimensions of organizations can moderate the nature of organizational leadership and its antecedents and consequences (Zaccaro and Klimoski 2002 ), scientific leadership research has been covering many of these aspects (Golden and Shriner 2017 ; Charbonnier-Voirin et al. 2010 ; Jensen 2013 ; Kulophas et al. 2015 ; Zubair and Kamal 2016 ). According to Antonakis and Atwater ( 2002 ), structural distance can be defined as physical structure (i.e., physical distance between leader and subordinate), organizational structure (e.g., hierarchical level, span of control), and supervision structure (i.e., frequency of leader-subordinate interaction). In this work, research participants’ affiliation to a specific organizational setup (in-house vs. sales staff) of the collaborating pharmaceutical company is treated as context variable. Its moderating effect on various leadership-consequences relationships is analyzed. Especially the physical distance between leader and subordinate is structurally different in both work settings. When coming to TL’s and AL’s relationship with employee attitudinal and behavioral constructs, moderation analysis will be carried out on the basis of participants’ affiliation with one of the two work contexts. Moderation hypotheses in this work have the structure presented in Fig. 2 below.

Structure of hypothesized moderator effects. Source: Own representation

Social Identity Theory (SIT) postulates that individuals identify with social entities, e.g. individuals or organizations, to foster and maintain a positive self-concept (Tajfel and Turner 1986 ). Organizations offer employees a multitude of identification targets, so-called foci. These foci can be an organization as a whole, a team, or a manager (van Dick 2001 ). Positive leadership theories should be able to enhance subordinates’ identification with manager (IM). With respect to the IM construct, it is expected that both leadership models will contribute to employees’ Identification with Manager:

Authentic Leadership will be a positive predictor of subordinates’ Identification with Manager

Transformational Leadership will be a positive predictor of subordinates’ Identification with Manager

Moreover, it is hypothesized that the employees’ work context (i.e. organizational unit: in-house staff vs. sales) will have a moderating effect on the AL/TL-IM relationship:

The relationship between AL and IM will be moderated by employees’ work context (in-house staff vs. sales)

The relationship between TL and IM will be moderated by employees’ work context (in-house staff vs. sales)

According to West and Farr, Innovative Work Behavior (IWB) describes the intentional creation, introduction and application of new ideas within a work role, group or organization in order to benefit role performance, the group or the organization (West and Farr 1989 ). In line with previous research, it is expected that both leadership models contribute positively to employees’ IWB:

Authentic Leadership will be a positive predictor of subordinates’ Innovative Work Behavior

Transformational Leadership will be a positive predictor of subordinates’ Innovative Work Behavior

Moreover, it is postulated that employees’ work context, i.e. their affiliation to in-house vs. sales teams, will moderate the AL/TL-IWB relationship:

The relationship between AL and IWB will be moderated by employees’ work context (in-house staff vs. sales)

The relationship between TL and IWB will be moderated by employees’ work context (in-house staff vs. sales)

Rousseau et al. ( 1998 ) comprehensively describe the nature of the trust construct: “Trust is a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intentions or behavior of another” (p. 394f). It comprises both exchange processes and an understanding of trust subjects and objects not limited to an individual. For the purpose of this research, focus is on the interpersonal aspect of trust between manager (trust subject) and subordinate (trust object). According to Bass’ expansion of Burns’ TL theory, loyalty is an outcome of TL, mediated by trust, honesty and further qualities of the leader. This connection is substantiated in recent studies (e.g. Monzani et al. 2016 ). Overall, both leadership models are hypothesized to positively contribute to employees’ Trust and Loyalty (T&L):

Authentic Leadership will be a positive predictor of subordinates’ Trust and Loyalty

Transformational Leadership will be a positive predictor of subordinates’ Trust and Loyalty

Again, employees’ work context (in-house staff vs. sales team) is expected to moderate the AL/TL-T&L relationship:

The relationship between AL and T&L will be moderated by employees’ work context (in-house staff vs. sales)

The relationship between TL and T&L will be moderated by employees’ work context (in-house staff vs. sales)

Employee satisfaction (ES) is a construct frequently correlated with leadership in empirical research. Wong and Laschinger ( 2013 ), for example, established a direct positive relationship between AL and ES. Yang et al. ( 2011 ) confirmed a positive relationship for TL and ES. In this work, a positive relationship between both leadership models and subordinates’ ES is postulated:

Authentic Leadership will be a positive predictor of subordinates’ Employee Satisfaction

Transformational Leadership will be a positive predictor of subordinates’ Employee Satisfaction

Employees’ work context (in-house staff vs. sales team) will have a moderating effect on the AL/TL-ES relationship:

The relationship between AL and ES will be moderated by employees’ work context (in-house staff vs. sales)

The relationship between TL and ES will be moderated by employees’ work context (in-house staff vs. sales)

4 Empirical Assessment of the Models

The statistical software IBM SPSS Statistics 21 including the macro PROCESS (Version 3.1) was used to test the hypotheses (Hayes 2013 ). In total, 5 hierarchical regression analyses were conducted, consisting out of subsequent, identical steps for each of the five dependent variables. PROCESS Matrix procedure was also chosen to define and analyze the models evaluating moderating effects. Tests of unconditional interactions between independent variables and conditional effects of focal predictors in accordance to values of the moderators are possible.

Data collection for this research project occurred through an online questionnaire activated from June 17th until/including July 15, 2018. Participating functions were employees and their first line managers from selected sales, marketing, market research, market access, medical management, patient care, human resources, communication and further business support teams. N = 247 employees, thereof N = 34 first line managers, were invited. To avoid respondents’ overload, a maximum duration of 15 min per survey is recommended (Batinic and Bosnjak 2000 ). With an average residence time of a bit longer than 11 min this threshold level was met. N = 143 employees clicked through the entire questionnaire. After initial exploratory descriptive data analysis using SPSS, N = 6 respondents were excluded due to missing data for four or more constructs. All final data analysis is therefore based on N = 137 respondents. Consequently, the ratio of evaluable cases vs. invited employees (N = 247) is 55%. Of N = 137 participants, 79 (58%) are female, 58 (42%) are male. The online cohort should quite closely reflect the workforce structure of companies of the healthcare sector. Regarding age distribution, the online cohort matches the national distribution of the German working population very well. An important variable is the affiliation of employees to in-house vs. sales personnel. In our sample, respondents are almost equally split between in-house based (N = 76; 55%) and sales employees (N = 61; 45%).

For the operationalization of AL, the ALQ (Authentic Leadership Questionnaire) as a well-established, theory-driven and validated measurement scale was chosen (Walumbwa et al. 2008 ). For the purpose of this research, a German translation of the ALQ, validated by Peus et al. ( 2012 ), was used. The version for external assessment from employees’ perspective was applied. Internal consistency alphas (Cronbach’s α) for each of the four subscales and the overall scale were originally reported to be higher than 0.7 in a cross-cultural validation study (Walumbwa et al. 2008 ). In the present project, SPSS data analysis shows a high Cronbach’s α of 0.94 for the overall ALQ construct. Responses were collected on a 5-point Likert scale with pre-determined answer options ranging from (1) “Does not apply at all” to (5) “Fully applies”; German translations were used, respectively.

TL is operationalized by the GTL (Global Transformational Leadership scale). This short measure was tested, validated and confirmed by many studies in various geographical and business contexts (Carless et al. 2000 ; van Beveren et al. 2017 ). In the present analysis, Cronbach’s α of 0.90 confirms its internal consistency. As in the original study, the response format was a 5-point Likert scale ranging from (1) “Does not apply at all” to (5) “Fully applies”.

Based on an instrument for Organizational Identification (OI) from Mael and Ashforth ( 1992 ), Ullrich et al. ( 2009 ) developed a short measure for IM consisting of three items. The original Cronbach’s α was .69 (Ullrich et al. 2009 ). Similar to organizations, teams or workgroups, managers can represent a social category with which employees identify themselves (Gautam et al. 2004 ). Therefore, the original OI instrument was amended to an IM scale. In the present research, a Cronbach’s α of 0.84 was reached. Consistent with the previous measurement constructs, a 5-point Likert scale with identical response options was used.

IWB is assessed by nine items derived from Scott and Bruce’s ( 1994 ) scale. It has also proven validity and reliability in the work of Janssen ( 2000 ). In accordance to the theoretical concept described earlier, three items each refer to the aspects of idea generation, idea promotion and idea realization. Again, a 5-point Likert scale was applied. Response options now ranged from (1) “Never” to (5) “Always”. Janssen ( 2000 ) reported a Cronbach’s α of 0.95 for this instrument. The present data set delivers a very acceptable Cronbach’s α of 0.90.

Trust in and loyalty to the leader is operationalized by use of a six item scale of Podsakoff et al. ( 1990 ). The first three items represent the trust component of the instrument. In turn, the remaining three items stand for employees’ sense of loyalty to their managers. Again, responses were collected on a 5-point Likert scale with answer options of (1) “Does not apply at all” to (5) “Fully applies”. In our data set a Cronbach’s α of 0.93 was reached, pointing to a very good internal consistency.

Additional constructs like Organizational Identification (OI) and Employee Satisfaction (ES) considered in the comprehensive work were operationalized by a validated 3-item scale from Mael and Ashforth ( 1992 ) and a five-item short instrument based on an original scale developed by Brayfield and Rothe ( 1951 ).

Hypotheses H 1a to H 8a are tested by application of regression analysis. Hierarchical Regression analysis is applied to evaluate the differential explanatory effect of both Leadership Models, AL vs. TL. Four three-step hierarchical regression analyses were run with the following dependent variables: IM, IWB, T&L and ES. At step one of each of the separate calculations, the demographic variables age and sex were entered to control for covariates. AL was entered at step two as first predictor of conceptual interest. The second predictor TL was entered at step three. The variables were introduced stepwise to see if they have an effect over and above covariates.

Table 1 shows the Means, Standard Deviations, Cronbach’s α for all constructs covered, as well as Intercorrelations.

Due to limited space, not all statistical analyses are presented in detail. Of course, all analyses and their results are available when contacting the authors. As age and gender might have effects on the dependent variables of interest, they were entered in the analyses as control variables.

TL explained additional variance above and beyond AL in Identification with the Manager, Trust and Loyalty in the leader, and Employee Satisfaction (confirmation of Hypotheses H 1a , H 2a , H 5a , H 6a, H 7a , H 8a ). However, neither AL nor TL explained significant variance in Innovative Work Behavior (rejection of Hypotheses H 3a , H 4a ,).

Nevertheless, when context was included inside the model (moderator: in-house vs. sales), there was a positive relation between AL and innovative work behavior for sales, but not for in-house staff (see Fig. 3 ). Additionally, the moderator analyses revealed that the relation for both AL and TL and trust and loyalty towards the leader was stronger in sales than in in-house staff (see Figs. 4 and 5 ). Consequently, hypotheses H 3b , H 5b , H 6b are confirmed. Hypotheses H 4b , as well as H 7b and H 8b on moderating influences of context on the relationship between AL/TL and ES are rejected, though.

The moderating influence of work context on the AL-IWB relationship. Source: Own representation based on SPSS analysis

The moderating influence of work context on the AL-T&L relationship. Source: Own representation based on SPSS analysis

The moderating influence of work context on the TL-T&L relationship. Source: Own representation based on SPSS analysis

5 Summary, Implications and Outlook

Key objective of this work was to empirically test the relationship between leadership and its key consequences. By means of an online survey with 137 employees of a pharmaceutical company in Germany, the importance of positive leadership models–Authentic and Transformational leadership–for the occurrence of desirable work attitudes and behaviors like Identification with Manager, Trust and Loyalty, and Employee Satisfaction, was documented. This implies that in corporate practice a positive leadership culture is suitable to stimulate relevant employee actions that contribute significantly to corporate success.

Based on a comprehensive literature review, AL and TL were identified as the main contemporary leadership models of interest. Consequently, these approaches constituted the key independent variables entered both into multiple hierarchical regression as well as moderation analysis models. As a secondary objective, the empirical analysis shed light on the pharmaceutical industry sector and expanded scientific knowledge regarding consequences and potential moderating effects of work contexts.

Essences of the present empirical research are:

Positive Leadership Behaviors (AL and TL) are positive predictors of critical employee attitudes and business targets like Identification with Manager, subordinates’ Trust and Loyalty, and Employee Satisfaction.

The empirical research results confirm construct validity and conceptual independence of both positive leadership theories, AL and TL.

Work context, operationalized as in-house vs. sales personnel, significantly impact some leadership-consequences relationships, i.e. leadership’s relationship with Trust and Loyalty is significantly moderated by work context (with a stronger effect in the study population of sales force); for the AL-IWB relationship, a significant moderating effect for sales personnel was also confirmed.

Although an often stated need for quantification of positive leadership behavior in corporate financial success and target figures was not subject of this investigation, the confirmed relationships between positive leadership and most of the desirable work attitudes and behaviors indicate that AL and TL contribute positively to operating profit.

In addition to the above mentioned financial aspects, hints on positive aspects of employee behavior, namely Innovative Work Behavior, could be derived. As this was especially accentuated in the context of customer facing sales personnel, one could infer that high AL in sales contexts can have a halo effect on sales reps customer interactions.

In order to achieve corporate goals, a recommendation to pharmaceutical companies is to establish a corporate culture that fosters positive leadership behavior. Leader recruitment, leadership training and development should take the “4 I’s” of TL and the four aspects of AL as a reference. Specific examples for HR departments can be to provide platforms and trainings for people managers to develop capabilities as mentors, coaches and active listeners. In order to be able to act as a positive role model for employees, leaders should be clear about ethical and moral standards, also with regards to the specifics of the pharmaceutical industry. Moreover, tools to foster leaders’ and employees’ self-awareness, a culture that supports transparency and one of error tolerance would be very beneficial to establish the desirable leadership styles, hence positive employee attitudes and behaviors.

Although this research shows promising results, a few limitations need to be mentioned. First, this study has a cross-sectional design. Therefore, longitudinal investigations could be of interest in order to evaluate intrapersonal developments over time and if and how they impact job attitudes and behavior. Second, due to requirements of the collaborating company’s works council in order to ensure anonymity and maximum data protection, a dyadic approach to collect and analyze data based on team structures was not allowed. It would be advisable for future research to collect and use this information in order to enhance data quality and model reliability by reducing a potentially high amount of additional variance. Similarly, the actual duration of individual leader-subordinate relationships could actively be controlled for, as interpersonal relationships including the development of trust tend to evolve over time. Third, all outcome variables are solely based on employee self-assessment. This potential for common source bias could be reduced in future studies if additional sources of feedback and information can be taken into account, e.g. supervisors’ evaluations of employees’ behavior or secondary data from more objective performance evaluations. Fourth, the present moderation analysis is purely based on self-reported organizational allocation to in-house vs. sales departments. This was used as a surrogate for work context, primarily reflecting physical distance to the supervisor, which in turn was supposed to impact frequency and quality of communication. However, quality of leader-subordinate interaction might be perceived quite differently on a personal level. In future studies, analysis could therefore be controlled for effective communication frequency and/or perceived quality of communication channel and content of leader-subordinate exchange.

Despite these limitations and implications for future research, the study provided various important insights. It seems to be first research project to systematically analyze the two contemporary positive leadership models Authentic Leadership and Transformational Leadership in a comparative context of in-house staff and sales representatives of a single pharmaceutical company in Germany.

In order to build on the current outcomes, the following direction for future research can be proposed. First, a longitudinal study design could be chosen to be able to track the development of interpersonal leader-subordinate relationships over time. Second, recourse to potentially more objective multi-source data to substantiate the expressed employee attitudes and behaviors might be beneficial. Third, the study could be run in or across different companies and industries to detect significant differences or communalities. Similarly, the study could be replicated by inclusion of different hierarchy levels within companies to assess if team size or span of control impacts the relationship of leadership and its consequences. Fourth, the evaluation of antecedents of AL and TL could be added to the research design to potentially derive implications for people management and personnel development.

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Lange, M.A., Hernandez-Bark, A. (2020). Leadership Models and Work Behavior: An Empirical Analysis of Consequences of Authentic and Transformational Leadership. In: Schweizer, L., Dingermann, T., Russe, O., Jansen, C. (eds) Advances in Pharma Business Management and Research. Springer, Cham. https://doi.org/10.1007/978-3-030-35918-8_6

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Systematic Review

A systematic review of literature about leadership and organization.

Received: April 19, 2018;   Accepted: June 26, 2018;   Published: February 26, 2019

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Introduction.

From trait theory, through human relations school of thought, to contingency and/or situational model, leadership research has come a long way 1 . However, as observed by Wren 2 , still very little is known about leadership and much remain unexplained. Around a century back, Stogdill 1 remarked, “There are almost as many different definitions of leadership as there are persons who have attempted to define the concept”. More recently, while commenting on the huge number of articles written about leadership, Winston and Patterson 3 state that there seem to be a lot of blind men describing a moving elephant. Winston and Patterson 3 further remark that even 90+ dimensions of leadership are not sufficient enough to understand leadership. Such has been the history of leadership research that no clarity or consensus about its definition, styles, effective methods, etc., could emerge in the literature even after centuries of research.

During the last two decades or so, focused research about leadership issues has started gaining ground 4 . The field is now starting to take a rather holistic view of leadership as a result of which more positive forms of leadership are getting incorporated into the literature. This can mainly be attributed to the introduction and popularity of focused yet holistic journals in the field of leadership.

The journal covered under this article has emerged as one of the most regarded journal in the field of leadership research. While most of the prominent journals focus on either of organizational or leadership issues, this journal takes a coherent view and attempts to understand the effective application of leadership and other issues in an organizational context. Its vision of advancing the theory, research and practice of all aspects of leadership and organizations, makes the journal attract a wide range of contributors and readers from academia and corporate world. In order to inform the researchers and readers about the directions in the integrated field of leadership and organizational research, this paper systematically reviews the research papers published in the journal between 2010 and 2017 and makes an attempt to set-up the research agenda for future.

This paper uses the methodology of systematic review. Presenting a critique of reviews conducted in the field of Management research, Hart 5 maintains that those are usually narrative and biased as per the implicit biases of the researcher. This view is also supported by Davies 6 , Sharma and Bodla 7 , Sharma and Sanchita 8 . Davies 6 further argues that systematic reviews help overcome these limitations by bringing out the consistencies and variability’s of studies reviewed. In their landmark work on the methodology of systematic reviews, Tranfield et al . 9 stress upon producing a reliable knowledge stock by developing context-sensitive research. This paper follows the methodological rigor suggested by Tranfield et al . 9 .

THEORETICAL FRAME OF REFERENCE

Intended to recognize the key themes in reviewed literature, the authors conducted a systematic analysis of 208 papers published during 2010 to 2017 10 - 14 . For current study, the broad areas were leadership motivation, leadership excellence and leadership communication. These subjects were further divided into following topics:

Effect on job performance and work satisfaction: Taking into consideration the themes of the reviewed literature, this paper briefly presented these topics in the following sub-sections. It was important to emphasize that the objective of this section was not to discuss the main topics in leadership and organization but rather to present the themes explored by papers published during the selected time-frame.

Leadership style in general: Successful leader was one who can influence the followers to achieve the organizational objective. Different leadership styles affect the organizational and employee performance differently 15 . Leadership style did;//mz affect the culture of the concern, thus its efficiency. Leadership is a process of influencing the followers socially so that they can participate intentionally to achieve the organizational objective 16 . Leadership style can affect organizational commitment and work satisfaction explicitly and work satisfaction can further positively affect organizational commitment and work performance. The perception of employees about the transactional and transformational leadership style has a high degree of correlation with the motivation factors of the leader in the organization. The style of leadership has an impact on satisfaction level and trust in the leader. Organizational citizenship behavior directly influences the relation between style of leadership and commitment towards the organization 17 .

Leadership style can be divided into two broad types, namely transformational and transactional. A transformational leader is one who is influential, innovative and encourages others. This type of style creates an open and trustworthy culture, which motivates them to achieve the goal 18 . Transactional leader focuses on supervision, organization and performance. Both reward and punishment have used as a tool to encourage the followers to fulfill the required task. In the current scenario an organization needs a leader who can understand the demand of a complex environment. The relation between the leader and an employee and the leadership style enhances the satisfaction level of the follower.

Moderating factors in leadership: Moderating variables in leadership had drawn attention in the recent research. A number of theories had explored the moderating effects of variety of factors like subordinate, work and psychology on the relation between leadership and effectiveness. Knickerbocker 19 projected a theory of leadership that emphasized on the needs of the employees’.Knickerbocker 19 maintained that a coordinated relationship between the team members was required to achieve the target of a team, which could be achieved by presence of a leader. His opined that leadership effectiveness was dependent on the need of the employees. In contrary to this theory, De Vries et al . 20 explored the moderating role of need for the leader and found that higher urge for leader showed weaker relation between work stress of employees and task oriented leader. De Vries et al . 20 further maintain that high task oriented leader makes the employee feel more pressurized and thus leads to stress. The need for leadership was related to the characteristics of a leader. The study raised two important questions-(a) when the employees need support of a leader, do they show and (b) would the leader change the style of motivation and inspiration depending on the need of the employees.

Quitting intentions and leadership: To remain competitive in the dynamic business environment, holding on to the productive human resources and reducing the employee turnover, is the key. High turnover rate among employees can adversely impact the company in terms of high training cost, high selection cost, decreased productivity and low staff morale. Loyalty towards organization and leader, leads to positive intentions in employees to stay with the organization for long time 21 . Transformational leadership were found to be negatively related to employees’ voluntary organizational turnover intention, on the other side availability of job opportunity did not affect the transformational leadership and turnover intention 22 . Long et al . 23 remark that transformational and transactional leadership styles had negative impact on quitting intention. Puni et al . 24 found a positive association between autocratic leadership style, quitting intentions and counterproductive work behavior and a negative relationship between democratic leadership style, quitting intentions and counterproductive work behavior. Puni et al . 24 further noted that the leaders using laissez faire style yield negative relation with quitting intentions but positive with counterproductive work behavior. Further, the study observed that in autocratic style of leadership, a leader emphasized more on productivity than on people due to which employees’ quitting intentions increased dramatically.

Leadership perception: The climate and organizational environment highly depends on the perception of leaders, managers and employees. Perception was a difficult part of human behavior, the perception of different individual need not to be same. In the context of organization it became difficult to accomplish objectives when leaders and followers had very different perception 25 .

In today’s organizational perspective employees expects leader to be people oriented as they consider team work, relationship building as a basic pillar for organizational management. Madden 26 in his study found that there was a stereotype that women were insecure, over controlling and enable to engage in team play. Helgesen 27 argued that women were relationship oriented, non-hierarchical and take interest in sharing power and information.

Perception which was negative can lead to wrong decision and it could be dangerous for the leaders well as organization. Understanding the perception was a process in which the leader needs to analyze the situation and information in a rational manner. Listening and communication skills of leader lead to deal with the situation more empathetically and efficiently.

Role in learning: The competency of a leader in terms of technical proficiency is positively related with the employees’ creativity and learning behavior. In addition to these learning acts as a mediator between innovativeness of employees and competencies of the leader 28 . The transformational leaders enhance creativity in employees. Therefore, companies prefer such candidates as leaders who possess these skills or at least have the potential to become one.

Brown and Posner 29 found that leadership development programs and approaches should accomplish at personal and emotional level which furthers enhance insights about self and helps in creating learning and leadership mind sets. Transformational learning theories could be used to help and develop transformational leader.

Effect of leadership on job performance and work satisfaction: Saleem 30 observed that transformational leadership style increased job satisfaction among employees while transactional leadership leaves a negative impact on job satisfaction of employees. Goleman 31 suggests, “a leader should hold each leadership style in his bag like a golfer and he should be well averse to know that what style he should use in which situation because at every round of golf, you cannot use the same ball”. It is important to know that contingency theories play an important role in enhancing the job satisfaction.

Rad and Yarmohammadian 32 concluded that employees showed less satisfaction with salaries, benefits, promotion and communication and they will more satisfied with type of job and good supervisor. They proved significant correlation between the leadership behaviors and employees and job satisfaction. Good relationship with staff increases the satisfaction level of employees; however, situational leadership can negatively impact job satisfaction of employees.

METHODS AND RESEARCH TECHNIQUES

This paper systematically reviews 208 papers published on leadership and related areas from 2010 through 2017. As shown in Fig. 1 , out of 208 papers selected for study, 33 were out of context so they have been rejected, 56 papers have been rejected on the ground of not being related to the topic. Finally 119 papers used for further systematic review which were related to leadership studies.

By summarizing the issues addressed by the journal during the reference period, the paper provided valuable insights to the current researchers about the research gap and future research areas of leadership 9 . This research was divided into five major tasks:

Research mechanism and implementation: To get the miniature view of the articles studied for this systematic review, the authors had tabulated the leading points by coding each distinct feature.

Some of the articles have also covered more than one subject or domain so, multiple codes have also been assigned to the article on different key areas. Table 1 depicted that first classification of codes had been based on the context. The culture of every country was different, so was their management view of getting the things done and their leadership style. A motivation or leadership technique that had been proved successful in one country may not be replicated in another country. In this classification of context, the countries were categorized into four series, i.e., developed country, developing and emerging country, under developed country and if the research was not specifically done in/or for a particular country then it was categorized as not applicable. The codes A to D had been used to classify the context to the research.

The next classification in Table 1 had been done on the basis of the geographical region. For the purpose of coding, seven geographical regions have been used, namely-USA, UK, France, Germany, China, India and Islamic countries represented by code A to G respectively. Code H had been assigned to the papers not belonging to any of these countries. In case, research was not country specific then I code was used.

The third classification was done on the basis of the objective of the study. Code A was assigned to the empirical studies, in which direct or indirect observation had been used to gain the knowledge. For case study method, code B was assigned. If the article makes theoretical and methodological contributions to the topic, it came under Code C. Code D was used for conceptual study, while code E has been assigned to the studies not falling in the above categories.

Main subject of the research articles reviewed forms the basis for the fourth classification. The papers were coded as A, B, C and D. It depicts the focus point of the study on which the research article is based. The key subjects taken for the systematic review were leadership motivation, leadership excellence and leadership communication and others.

Fifth classification had been done on the basis of the main topic of the research. This classification further narrows down the research area that had been chosen in fourth category. Codes ranging from A to I have been assigned. It includes topics resembling leadership style in general, moderating factors, quitting intentions, leadership perception and role in learning, effect on job performance, work satisfaction, virtual leadership and others.

The sixth classification makes an attempt to categorize the leadership style evaluated in the papers coded as letter A to H. This categorization holds significance since style provides direction, helps implement the plans and motivates people. Besides giving codes to seven styles of leadership, one code is assigned to a category where no particular style is studied.

Industry studied, forms the base for the seventh classification. Leadership style, the way of working, culture and organizational structure is not common across industry. So, this part has been divided into four categories, namely-manufacturing, service, trading and others. Codes have been assigned from A to D, respectively.

Eighth classification depicts the time period of the research. Time period of research was taken as very crucial distinction in research design categorization. This category had been divided into five codes ranging from A to E. A was assigned to the articles with time-frame of less than one year, B depicts 1-5 years, C is assigned to papers with time frame of 6-10, years followed by D for more than 10 years. E was assigned to the articles where the time period was not applicable.

Ninth classification involves identifying the research methods used for research. Codes A to G have been assigned to this category. It was important to classify whether research is qualitative or quantitative. Other categories in this classification include conceptual method, case study and others if a research paper does not fall in the given category.

The tenth classification reveals the sample size of the research article. By sample size, the authors recognize a group of subjects that is selected from the population. For this category, the codes range from A to D. A category covers articles with sample size of less than 50, B category includes sample size of 51-100, C category is for more than 100 and D category covers the papers not falling in any of the above categories.

The eleventh classification relates to the size of the industry and is coded from A to C. Large scale industry is coded by A, small and medium industry by B, while others are coded as C. Size of the industry is important to categorize as different sizes of industry show different types of results since the number of employees, decentralization level, span of control is not same in each size.

Lastly, the twelfth category highlights different aspects of the results from the articles under review. This category had been divided into five codes ranging from A to E. In this coding, attempt has been made to seek the results of articles based on the information gathered. It included whether the results were consistent with previous literature or does it offer a new perspective.

RESULTS AND DISCUSSION

This section revealed the data classification and categorization of 119 papers on the basis of codes assigned to those in the previous section. The results were produced in Table 2 followed by their analysis and interpretation. On the basis of results, research gaps had been highlighted for further research.

Context: The first classification identified the context of the papers under review. For the purpose of coding, the context was divided into four parts A, B, C and D. Code A was assigned to developed countries, code B for developing and emerging countries, for under developed countries code C was given and code D if it was not applicable to any of these. The results were shown in the form of pie chart in Fig. 2 .

As depicted by Fig. 2 , majority of the studies 14 , 17 , 22 , 26 were not country specific. None of the reviewed studies focused on underdeveloped countries, 13.45% of the studies 18 , 21 deal with developed countries, 5.88% studies had been done in the context of developing and emerging countries, while 5.04% of the research articles belong to the context of both developed and developing and emerging countries. This revealed that studies on leadership and organizational issues pertaining to the underdeveloped country were lacking. This indicated a major research gap that needs to be investigated in future research.

Geographical area: For this category, seven geographical regions have been used namely USA, UK, France, Germany, China, India and Islamic countries represented by codes A to G respectively. Code H is assigned to the papers that do not belong to any of these countries. In case research was not country specific, code I is used. Figure 3 shows the analyses of codes based on the geographical area. Figure 3 showed that majority 19 , 22 , 25 of research articles (75%) were not specific to any geographical area, 6% of the studies belong to USA and 8% deal with other countries, 5% research articles focus on China, while 1% do not belong to any of these countries.

Objective: The third classification refers to identifying the objectives of the analyzed papers. Code A is assigned to the empirical studies, code B is assigned for case study method, code C is assigned to the articles based on theoretical and methodological contribution, code D is used for conceptual studies focusing on concept or theory explaining the phenomenon, code E has been assigned to studies belonging to any other category. The results as shown in Fig. 4 revealed that 69% of the reviewed papers 14 , 16 , 17 , 22 , 24 , 26 employ the empirical method, while 18% were conceptual studies, 6% use case study method and literature review.

Main subjects: The next classification was based on the main subject of the research articles reviewed for systematic review as A, B, C and D. It depicts the focus point of the study. The key subjects taken for the coding are leadership motivation, leadership excellence, leadership communication and others. As shown by Fig. 5 , the main focus of maximum research in the articles studied 18 , 22 , 26 was on leadership excellence (29%). 4% of the articles are relate to leadership motivation and 4% to leadership communication.

The remaining articles focus on other than the given subjects. The combinations studied are leadership motivation and excellence (5%), Leadership excellence and others (8%). The analysis of main subject shows that there are certain avenues open for the researchers in study of leadership motivation and leadership communication, though the previous researchers have focused on leadership excellence.

Topics: This classification was based on identification of the main topic of research. The codes assigned for this category range from A to, I. This classification further narrows down the research area t chosen in the previous category. It includes topics resembling leadership style in general, moderating factors, quitting intentions, leadership perception and role in learning, effect on job performance, work satisfaction, virtual leadership and others.

As shown in Fig. 6 , many code combinations had got developed while analyzing the papers for this category. The topics emerged during the research were the combination of two or more subjects. About 6% of the papers focused on moderating factors and effect on job performance, 8% study other factors along with moderating factors, 5% cover effect on job performance, work satisfaction with grouping of other topics. All the other combinations of codes contribute to only 1%. Only few articles focus on a single topic.

Leadership style evaluated: This classification is an attempt to categorize the leadership style evaluated in the papers studied, coded from A to H ( Fig. 7 ).

Besides giving codes to seven styles of leadership, one code is assigned to a category where no particular style is being evaluated. Majority of the studies (71%) do not concentrate on any particular leadership style, 15% of the articles evaluate transformational leadership style, 3% of the papers study mixed style and remaining researchers study combination of two or more styles.

Type of organization: This classification shows the categorization on the basis of industry. This part has been divided into three categories Manufacturing, Service, Trading and others. Codes have been assigned from A to D respectively. 21% articles focus on service industry, while 76% articles have not chosen any specific type of organization for their research. Figure 8 exhibits the results with regard to this classification.

Time period: The eighth classification depicts the time period of the research as exhibited in Fig. 9 . This category has been divided into five parts assigning codes from A to E; A- less than 1 years, B-1-5 years, C-6-10 years, D-10 years and more, E for the articles where time period is not applicable.92% percent of the articles do not cater to any specific time period, 5% articles base their analysis on less than one year, 2% of the research articles are based on 1-5 years of category.

Method: This category of classification involved identifying the research methods used for research as plotted in Fig. 10 . Codes from A to G had been assigned in which quantitative, qualitative, conceptual, quantitative and qualitative both, case study and none of these categories had been coded. About 42% of the papers use quantitative methods, 28% papers employed both quantitative and qualitative methods, 18% articles used conceptual method.

Sample size: This classification revealed the sample size of the articles analyzed as shown in Fig. 11 . For this category, codes ranged from A to D. A category contains the articles with sample size of under 50, B category comprises of papers with sample size of 51-100, C included papers with sample size of more than 100, D included papers other than these. Majority of the articles (52%) use the sample size more than 100, 40% articles fall in others category where sample size was not applicable, 6% articles had used sample size below 50.

Size of the industry: This classification related to size of the industry and the codes assigned ranged from A to C as shown in Fig. 12 . Large scale industry is coded by A, small and medium sized industry coded by B and others fall in category C. Most of the studies did not focus on analysis of a particular size of industry, 11% analyze the large industries, 2% focus on small and medium enterprises.

The last category ( Fig. 13 ) highlighted different aspects of the results of the research articles studied. This category had been divided into five codes ranging from A to E. It included whether the results were consistent with previous literature or leading to a new perspective, was it a previous model with different data set and time period, comparative study and others.

Majority of the articles (52%) present comparative analysis, 9% articles deal with each of category B and C that was consistent with previous literature and previous model with different data set and time period.

CONCLUSION AND FUTURE RECOMMENDATIONS

The main contribution of the current paper was to summarize the issues addressed by these articles and to bring out the research gaps. The current study explored 119 articles which were purely devoted to the study of leadership and organization. On the basis of the gaps explored, it can be stated that the research arena is wide open for the future research in the area of leadership and related areas that can be explored by novel research. The current research found that the future researchers can focus on underdeveloped countries and explore how leadership in organizations of underdeveloped countries can meet current and future organizational challenges. The future researchers can focus on conducting research in specific regions and explore the influence that leadership has on organizations of different regions. Future research can also focus on meta-analysis and explore the significance of case study/literature review or comparative analysis in addressing leadership problems in organizations. With respect to main subject of the study, it is found that most of the studies focus on leadership excellence whereas research on leadership motivation and communication is lagging behind. Therefore, future research can examine how leadership motivation and communication can help an organization achieve its results. It is vital to explore how an organization from a specific sector manages and motivates its employees through effective leadership. Future research can focus on other techniques that can justify the objective of leadership study.

SIGNIFICANCE STATEMENT

This study holds immense significance for two core reasons. One, the paper consolidates the existing literature about leadership and organization. Two, the paper brings out the research gaps and sets a research agenda for future researchers in the field. The organic contribution of the authors is in listing out (a) the objectives that can be pursued by the future researchers, (b) the methodology that can be adopted by the future researchers, (c) the tools that can be put to use while researching in this area and (d) the industry that the future researchers may emphasize upon.

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Leadership Research Paper Topics

The exploration of leadership research paper topics is a vital task for students studying management. These topics delve into the theory and practice of leadership, offering valuable insights into the dynamics of organizational success. The following guide provides a comprehensive list of leadership research paper topics categorized into ten areas, from leadership theories and styles to the role of women in leadership. This guide will also discuss the breadth and depth of leadership as a research area, advise on how to choose the right topic, and share tips on writing an excellent leadership research paper. We will then introduce the custom paper writing services offered by iResearchNet, which can provide expert, tailored assistance for any leadership research topic. The text concludes with a compelling call-to-action, encouraging students to leverage iResearchNet’s services for their research paper needs. The central aim is to facilitate students’ journey in leadership studies, fostering academic growth and development.

100 Leadership Research Paper Topics

Studying leadership calls for a comprehensive variety of topics, reflecting the broad and deep nature of this area of study. This section presents a vast array of potential topics, categorized into ten key areas, each featuring ten unique subjects for investigation. This presents a multitude of directions for students to dive deep into their leadership research papers.

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Get 10% off with 24start discount code, 1. leadership theories:.

• Analysis of the evolution of leadership theories from trait to situational theories.
• A comparative study of transformational and transactional leadership models.
• A deep dive into the contingency theories of leadership.
• A practical exploration of the path-goal theory in modern organizations.
• An examination of servant leadership theory’s applicability in non-profit organizations.
• Exploring the role of emotional intelligence in the framework of authentic leadership.
• Evaluating the impact of charismatic leadership on employee motivation and productivity.
• Adaptive leadership theory in crisis management: an exploration.
• A detailed study of the correlation between leadership theories and personality traits.
• Leadership theories’ applications and implications in team management and dynamics.

2. Leadership Styles:

• The implications of autocratic leadership on employee satisfaction and morale.
• How democratic leadership fosters innovation and creativity in the workplace.
• The role and effects of laissez-faire leadership in creative industries.
• An investigation of transformational leadership’s influence on organizational culture.
• Evaluating the impact of transactional leadership on performance metrics.
• Applicability and effectiveness of servant leadership in corporate settings.
• Pros and cons of paternalistic leadership in different organizational structures.
• An examination of strategic leadership in the rapidly evolving tech industry.
• Analyzing the effects of adaptive leadership in the complex field of healthcare.
• A correlation study of leadership styles and employee retention rates.

3. Leadership and Ethics:

• Ethical leadership’s role in shaping and promoting corporate social responsibility.
• Analysis of the ethical dilemmas encountered by leaders in healthcare organizations.
• How ethical leadership moulds and influences organizational culture.
• A study on the corporate scandals resulted from unethical leadership.
• The ethical considerations in leadership decision-making processes.
• The relationship between ethical leadership and employees’ moral judgments.
• A sector-focused analysis of leadership ethics in the banking industry.
• Measuring the impact of ethical leadership on brand reputation.
• Exploring the influence of ethical leadership on corporate sustainability strategies.
• Leadership ethics in political organizations: an in-depth study.

4. Leadership and Diversity:

• The impact of diverse leadership on an organization’s inclusivity.
• Cultural diversity’s influence on leadership styles in multinational organizations.
• A study on the challenges faced by women in leadership roles.
• Evaluating the role of leadership in promoting gender equity in corporate organizations.
• The effect of diverse leadership on fostering innovation in multinational corporations.
• An examination of racial diversity in leadership and its effect on corporate image.
• Understanding the benefits and challenges of age diversity in leadership roles.
• Unraveling the opportunities and difficulties faced by LGBT+ individuals in leadership positions.
• Leadership strategies to effectively manage and promote diversity in the workplace.
• Leadership diversity’s impact on corporate social responsibility initiatives.

5. Leadership in Different Industries:

• The pivotal role of leadership in tech startups’ growth trajectory.
• Leadership in the healthcare industry: navigating through challenges and seizing opportunities.
• An exploration of military leadership principles and their potential application in a corporate setting.
• Characteristics of effective leadership in the hospitality industry: a detailed study.
• The significance of impactful leadership in the functioning of non-profit organizations.
• Leadership strategies that drive success in the retail industry.
• The role of leadership in driving innovation in the automotive industry.
• The best practices of effective leadership in the education sector.
• The influence of leadership on team performance in professional sports.
• Defining the traits of successful leadership in the fast-paced entertainment industry.

6. Leadership and Change Management:

• Exploring the impact of transformational leadership on change management processes.
• The role of leadership in shaping and implementing successful change initiatives.
• Understanding the leadership styles most effective for managing organizational change.
• A detailed study on leadership’s role in overcoming resistance to change.
• Leadership in driving and managing technological change in digital companies.
• An examination of adaptive leadership during organizational restructuring.
• The correlation between strategic leadership and successful change management.
• Influence of leadership on change acceptance and adaptation among employees.
• The role of leadership communication in managing change effectively.
• Examining the impact of leadership in change management across different industries.

7. Leadership and Employee Motivation:

• Impact of transformational leadership on employee motivation and job satisfaction.
• How leadership can influence employee motivation through effective communication.
• An exploration of the relationship between leadership styles and employee motivation levels.
• How servant leadership enhances employee motivation and engagement.
• Evaluating the role of leadership in developing effective reward systems for employee motivation.
• Examining the effects of charismatic leadership on employee motivation.
• The influence of leadership behavior on intrinsic and extrinsic motivation.
• Leadership strategies for fostering a motivating work environment.
• How leadership can use job design to enhance employee motivation.
• The impact of leadership recognition on employee motivation and performance.

8. Leadership Development:

• Understanding the role of mentoring in leadership development.
• Examining the importance of continuous learning in leadership development.
• The impact of coaching on leadership skill development.
• Analyzing the effectiveness of various leadership development programs.
• The role of experiential learning in the development of leadership skills.
• Influence of leadership development on succession planning in organizations.
• Investigating the role of self-awareness in leadership development.
• Evaluating the role of feedback in the leadership development process.
• The impact of leadership development initiatives on organizational performance.
• Understanding the importance of emotional intelligence in leadership development.

9. Leadership and Organizational Culture:

• The role of leadership in shaping and sustaining organizational culture.
• Analyzing the influence of leadership style on organizational culture.
• A study on how effective leadership can instill a culture of innovation.
• Investigating the relationship between leadership and organizational culture in multinational corporations.
• Exploring the effects of leadership communication on organizational culture.
• How transformational leadership influences a culture of teamwork.
• The role of leadership in promoting an ethical organizational culture.
• The influence of servant leadership on organizational culture.
• Leadership’s role in the creation and management of a customer-oriented culture.
• The impact of leadership transition on organizational culture.

10. Leadership and Decision Making:

• The role of leadership in strategic decision making.
• The influence of different leadership styles on decision-making processes.
• Evaluating the impact of leadership on ethical decision making in organizations.
• An exploration of how leadership affects group decision-making processes.
• The role of leadership intuition in decision making.
• Leadership strategies for effective crisis decision making.
• The influence of leadership in data-driven decision making.
• The impact of transformational leadership on innovative decision making.
• Leadership and decision-making under uncertainty: a comprehensive study.
• How leadership influences employee involvement in decision making.

These varied topics allow students to explore different aspects of leadership, spanning theory, styles, ethics, diversity, industry specifics, change management, employee motivation, development, organizational culture, and decision making. The broad range enables students to select a topic that aligns with their personal interests and professional aspirations. This extensive list also gives students the freedom to narrow their focus and delve deep into a specialized area of leadership. Thus, creating a foundation for an insightful and meaningful research paper.

The Range of Leadership Research Paper Topics

Leadership is an inherently complex and multifaceted concept, embodying various dimensions of organizational functioning. It is a dynamic process involving influence, direction, and facilitation towards achieving a common objective. Therefore, leadership has a profound influence on the behaviors, attitudes, and overall performance of an organization, making it a fertile ground for extensive and diverse research.

The range of leadership research paper topics is vast, reflecting the wide-ranging implications of leadership in different contexts. This breadth allows students to delve into various aspects of leadership, from exploring various leadership styles such as transformational, transactional, autocratic, democratic, and servant leadership, to understanding their effects on team dynamics, employee performance, motivation, and job satisfaction.

For instance, research into the various leadership styles provides critical insights into how different approaches to leadership can influence an organization’s effectiveness. Transformational leadership, for example, emphasizes the leader’s role in inspiring and motivating followers, fostering innovation, and driving change. In contrast, transactional leadership focuses on clear role and task definitions, rewards, and punishments as motivational tools.

Moreover, the intersection of leadership and ethics is another prolific area of research. Ethical leadership explores how leaders can integrate ethical principles into their decision-making processes, cultivate ethical behaviors within their teams, and ultimately foster an ethical organizational culture. Research in this field can range from examining the influence of ethical leadership on employee behavior to investigating the strategies leaders can employ to navigate ethical dilemmas.

Diversity in leadership, a critical aspect in the current globalized business environment, offers another area of intriguing research potential. Diverse leadership promotes a plethora of viewpoints, encourages creativity and innovation, and enhances organizational adaptability. Research topics in this category can involve investigating the effect of diverse leadership on team performance, the challenges and strategies in managing a diverse leadership team, or understanding how leadership can promote diversity and inclusion within an organization.

Research on leadership in different industrial and organizational contexts also offers a wealth of research paper topics. This can include leadership in healthcare, exploring how leaders can effectively manage healthcare professionals, improve patient outcomes, and drive change in the healthcare system. Leadership in educational settings, examining how school leaders can impact educational outcomes, foster a conducive learning environment, and navigate the unique challenges in the education sector.

Leadership’s role in change management is another critical area of research. Change is a constant factor in any organization, and effective leadership is critical in navigating this change successfully. Research topics here can focus on the various leadership strategies in implementing change, the challenges leaders face in this process, and the critical role leadership plays in overcoming resistance to change.

The impact of leadership on employee motivation also provides a rich area for investigation. The influence a leader has on an employee’s motivation levels can significantly affect job satisfaction, productivity, and retention. Topics here can explore the different leadership strategies that can enhance employee motivation, the role of leadership in developing effective reward systems, or how leadership behavior affects intrinsic and extrinsic motivation.

Leadership development is another theme rich in research opportunities. The creation of effective leaders is crucial to an organization’s success. Therefore, investigating leadership development programs, the role of coaching and mentoring in leadership development, or the impact of leadership development initiatives on organizational performance are all meaningful research directions.

In conclusion, the diversity in leadership research paper topics allows students to explore and investigate various areas of leadership theory and practice. From understanding different leadership styles and their effects, to delving into leadership ethics, diversity, industry-specific leadership, change management, motivation, and leadership development, the possibilities are extensive. This breadth and depth enable students to gain a comprehensive understanding of leadership and its vital role in shaping organizational success. The explorative journey into these leadership research paper topics lays a robust foundation for future leaders, providing them with essential insights into effective leadership practices.

How to Choose Leadership Research Paper Topics

Choosing the right topic for a leadership research paper is a critical first step in the process of writing a top-notch research paper. The right topic is not just a subject you find interesting, but one that is unique, manageable, and relevant to your course of study. In this section, we provide ten comprehensive tips to guide you in choosing the best leadership research paper topic.

• Identify Your Interest : Start by identifying what aspects of leadership interest you the most. Are you more drawn to the psychological aspects of leadership, such as how leaders motivate their teams, or are you more interested in the organizational aspects, such as how leadership styles impact company culture? Personal interest in a topic can make the research process more engaging and the writing process more enjoyable.
• Brainstorm : Spend time brainstorming potential topics. Write down everything that comes to mind, no matter how broad or specific. This process can help you to identify potential areas of interest and narrow down your options.
• Research Existing Literature : Before settling on a topic, take some time to read up on existing literature in the field of leadership. This can help you to identify gaps in knowledge that your research could fill, or controversial issues that could be the focus of your paper.
• Consider the Scope : Consider the scope of your research paper. If it’s a shorter paper, you’ll need a narrower topic. Conversely, for a longer paper, you can choose a broader topic that you can explore in detail.
• Consult Your Supervisor or Peers : Discuss potential topics with your supervisor or classmates. They may offer a fresh perspective or suggest areas of interest that you hadn’t considered.
• Check for Resources : Ensure that there are enough resources available for your chosen topic. This can include books, peer-reviewed articles, and credible online sources. Having enough sources will make your research process smoother and more productive.
• Relevance to Your Course : The topic you choose should be relevant to your course and future career. For example, if you plan to work in the non-profit sector, you might choose a topic related to leadership in non-profit organizations.
• Flexibility : Be flexible with your topic. As you start your research, you may find that your initial topic is too broad, too narrow, or not as interesting as you thought. Don’t be afraid to refine and modify your topic as needed.
• Uniqueness : While it’s good to align with current research trends, strive for uniqueness in your topic. Don’t just rehash old studies; instead, seek to contribute something new and meaningful to the field of leadership research.
• Practical Implications : Lastly, consider the practical implications of your research. Good research not only contributes to academic knowledge but also has practical applications. Choose a topic that could potentially inform leadership practices in real-world settings.

In conclusion, choosing a topic for a leadership research paper involves careful consideration of your interests, the scope of the paper, available resources, and the potential impact of your research. While the process can be challenging, the result is a topic that you’re passionate about and invested in, which ultimately makes for a higher quality research paper. Remember, the topic you choose sets the foundation for your entire paper, so take the time to choose wisely!

How to Write a Leadership Research Paper

Writing a leadership research paper is an intricate process that requires careful planning, thorough research, and detailed writing. A well-written research paper not only demonstrates your understanding of leadership principles but also your ability to critically analyze information, formulate arguments, and present your ideas in a clear and coherent manner. Below are ten comprehensive steps to guide you in writing an outstanding leadership research paper.

• Understanding the Assignment : Before you begin the actual writing process, make sure you understand the assignment requirements. What is the length of the paper? What is the deadline? Are there specific sources or citation styles you need to use? Understanding these requirements will help guide your research and writing process.
• Choose a Topic : If you haven’t been assigned a specific topic, use the tips provided in the previous section to choose a suitable topic for your leadership research paper. Make sure it’s a topic you’re interested in and one that is relevant to the course.
• Conduct Preliminary Research : Conduct initial research to get an overview of your chosen topic. Use this research to refine your topic and formulate a preliminary thesis statement. This statement will guide your further research and help focus your paper.
• Develop a Thesis Statement : Your thesis statement should clearly express the main point or argument of your research paper. It should be concise, specific, and arguable. A good thesis statement will guide your research and provide a roadmap for your paper.
• Create an Outline : An outline helps to organize your thoughts and ensure that you cover all the necessary points. It should include an introduction, body paragraphs (each with a sub-point supporting your thesis), and a conclusion. Outlining can also help you identify gaps in your research or arguments.
• Conduct In-Depth Research : At this point, dive deeper into your research. Utilize various sources, including books, academic journals, reputable websites, and interviews. Remember to evaluate the credibility of your sources and to take detailed notes, including the source information for citation purposes.
• Write the First Draft : Using your outline as a guide, start writing the first draft of your paper. Don’t worry about making it perfect; focus on getting your ideas down first. Start with the body paragraphs, then write the introduction and conclusion.
• Revise and Edit : Review your first draft, looking for any inconsistencies, redundancies, or areas that lack clarity. Check the flow of your arguments, the strength of your thesis statement, and the organization of your paper. Also, ensure that each paragraph has a clear topic sentence and that it supports the thesis statement.
• Proofread : After revising your content, proofread for grammar, spelling, and punctuation errors. You can use proofreading software, but also consider reading your paper aloud or having someone else proofread it.
• Cite Your Sources : Lastly, properly cite all the sources you used in your paper. Ensure that your in-text citations and reference list comply with the citation style required for your assignment (e.g., APA, MLA, Chicago/Turabian, Harvard).

In conclusion, writing a leadership research paper is a step-by-step process that requires thorough research, careful planning, and detailed writing. It may be a challenging task, but it’s also an opportunity to deepen your understanding of leadership and hone your academic writing skills. With commitment, patience, and the right strategies, you can successfully write a high-quality leadership research paper.

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The pathway to academic success is not always straightforward, but you don’t have to tread it alone. Leadership is a vast and complex field, and developing a high-quality research paper on the subject requires time, effort, and a deep understanding of various leadership theories and principles. With iResearchNet by your side, you can make the process not only manageable but also enjoyable.

At iResearchNet, we excel at helping students elevate their research work, particularly in the field of leadership. Our team of expert writers is well-versed in the wide range of leadership topics and the nuances of writing a compelling and academically rigorous research paper. So, why not take advantage of the expertise and dedication we offer?

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Why Leadership Teams Fail

• Thomas Keil
• Marianna Zangrillo

In pursuit of strong performance, CEOs often overlook a critical factor in organizational success: the health of their leadership team. That’s a big problem, because a dysfunctional team can be a serious drag on strategy execution.

To learn more about the problems that affect leadership teams, the authors interviewed more than 100 CEOs and senior executives in a multiyear research program. They identified three main patterns of dysfunction: the shark tank, characterized by infighting and political maneuvering; the petting zoo, characterized by conflict avoidance and an overemphasis on collaboration; and the mediocracy, characterized by complacency, a lack of competence, and an unhealthy focus on past success.

This article helps leadership teams diagnose their dynamic and find ways to improve it.

And what to do about it

In their pursuit of strong performance, CEOs and executives often overlook a critical factor in organizational success: the health of their leadership team. That’s a big problem, because a dysfunctional team can become a serious drag on strategy execution and erode morale. Not only that, the health of a senior team can make or break a CEO’s tenure.

It’s not just who’s in the room—it’s how they behave together.

• TK Thomas Keil is a professor and the chair in international management at the University of Zurich, Switzerland. He is a partner at the Next Advisors.
• MZ Marianna Zangrillo is a partner at the Next Advisors.

Partner Center

This paper is in the following e-collection/theme issue:

Published on 14.8.2024 in Vol 26 (2024)

This is a member publication of University of Toronto

Leadership for AI Transformation in Health Care Organization: Scoping Review

Authors of this article:

• Abi Sriharan 1, 2 , MSc, DPhil   ; 
• Nigar Sekercioglu 2 , PhD   ; 
• Cheryl Mitchell 3 , PhD   ; 
• Senthujan Senkaiahliyan 2 , MHSc   ; 
• Attila Hertelendy 4 , PhD   ; 
• Tracy Porter 5 , PhD   ; 
• Jane Banaszak-Holl 6 , PhD  

1 Krembil Centre for Health Management and Leadership, Schulich School of Business, York University, Toronto, ON, Canada

2 Institute for Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada

3 Gustavson School of Business, University of Victoria, Victoria, ON, Canada

4 College of Business, Florida International University, Florida, FL, United States

5 Department of Management, Cleveland State University, Cleveland, OH, United States

6 Department of Health Services Administration, School of Health Professions, University of Alabama Birmingham, Birmingham, OH, United States

Corresponding Author:

Abi Sriharan, MSc, DPhil

Krembil Centre for Health Management and Leadership

Schulich School of Business

York University

MB Room G315

4700 Keele St

Toronto, ON, M3J 1P3

Phone: 1 3658855898

Email: [email protected]

Background: The leaders of health care organizations are grappling with rising expenses and surging demands for health services. In response, they are increasingly embracing artificial intelligence (AI) technologies to improve patient care delivery, alleviate operational burdens, and efficiently improve health care safety and quality.

Objective: In this paper, we map the current literature and synthesize insights on the role of leadership in driving AI transformation within health care organizations.

Methods: We conducted a comprehensive search across several databases, including MEDLINE (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCO), Business Source Premier (via EBSCO), and Canadian Business & Current Affairs (via ProQuest), spanning articles published from 2015 to June 2023 discussing AI transformation within the health care sector. Specifically, we focused on empirical studies with a particular emphasis on leadership. We used an inductive, thematic analysis approach to qualitatively map the evidence. The findings were reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines.

Results: A comprehensive review of 2813 unique abstracts led to the retrieval of 97 full-text articles, with 22 included for detailed assessment. Our literature mapping reveals that successful AI integration within healthcare organizations requires leadership engagement across technological, strategic, operational, and organizational domains. Leaders must demonstrate a blend of technical expertise, adaptive strategies, and strong interpersonal skills to navigate the dynamic healthcare landscape shaped by complex regulatory, technological, and organizational factors.

Conclusions: In conclusion, leading AI transformation in healthcare requires a multidimensional approach, with leadership across technological, strategic, operational, and organizational domains. Organizations should implement a comprehensive leadership development strategy, including targeted training and cross-functional collaboration, to equip leaders with the skills needed for AI integration. Additionally, when upskilling or recruiting AI talent, priority should be given to individuals with a strong mix of technical expertise, adaptive capacity, and interpersonal acumen, enabling them to navigate the unique complexities of the healthcare environment.

Introduction

Artificial intelligence in health care: overview.

Artificial intelligence (AI) technologies have gained significant momentum in health care, presenting a transformative potential across clinical processes, operational efficiency, decision-making, and workforce optimization [ 1 - 3 ]. The global AI market is projected to shift from US $14.6 billion in 2023 to a formidable estimate of US $102.7 billion by 2028 [ 4 ], unveiling a dynamic transformation of unprecedented scale. This investment, coupled with the engagement of nontraditional health care players such as Microsoft, Google, and Amazon and the convergence of technological prowess and health care innovation signaled by generative AI, will place the trajectory of AI in health care in a state of exponential growth [ 5 ].

Current investments in health care AI predominantly center on bolstering data capacity, enhancing computational power, and advancing methodological innovations in AI. This includes developing and testing AI models and algorithms tailored for precision medicine, drug discovery, clinical decision-making support, public health surveillance, operational optimization, and process improvement [ 6 , 7 ]. Notably, between August 2022 and July 2023, there were over 150 submissions of drug and biological applications incorporating AI and machine learning components to the US Food and Drug Administration, encompassing a wide array of therapeutic domains and developmental stages [ 8 ].

Yet the seamless integration of AI technologies into health care organizational settings presents a multifaceted challenge for health care leaders. This challenge arises from several factors, including the complex nature of AI models, the rapid pace of technological advancement, the imperative of regulatory adherence, ethical concerns surrounding data security and privacy, the risk of perpetuating racial and ethnic biases in data, the necessity of prioritizing human-centric approaches to patient care, and the intricate clinical workflows that must be navigated [ 9 - 15 ]. Furthermore, health care leaders are facing critical and intricate strategic decisions. They must discern which AI solutions merit investment while weighing the merits of in-house development against strategic partnerships with external vendors. Selecting the right vendors and defining the scope of collaboration is pivotal, as is devising a sustainable funding strategy to support both initial development and continuous innovation. Furthermore, they must confront the crucial question of whether to bring in new AI talent or bolster the expertise of their current workforce through upskilling. Each of these decisions will shape the trajectory of health care organizations as they navigate this transformative era. A report by Bain in 2023 revealed that although 75% of surveyed health system executives recognize AI’s potential to reshape the health care industry, only 6% have established concrete strategies related to AI [ 16 ].

The lack of strategy and strategic failures in AI integration not only have financial consequences for organizations but also erode trust among patients, providers, and organizations [ 17 ]. A prominent example is the collaboration between MD Anderson and IBM Watson, aimed at leveraging IBM Watson’s cognitive capabilities to combat cancer. This ambitious endeavor, however, incurred a substantial financial toll of over US $62 million for MD Anderson because of setbacks in clinical implementation [ 18 ].

Despite a growing body of AI literature, including toolkits such as Canada Health Infoway’s “Toolkit for AI Implementers” [ 19 ] and guidance from the US Department of Health and Human Services’ AI Task Force [ 20 ] and the UK National Strategy for AI in Health and Social Care [ 21 ], there is still insufficient scholarly attention on how leadership behavior guides AI transformation in health care. Existing reviews focus on AI in medical education [ 22 , 23 ], workforce impact [ 24 ], applications in clinical medicine [ 13 , 25 ], barriers to implementation [ 26 , 27 ], and ethical considerations [ 28 , 29 ]. However, no systematic mapping of empirical literature has clarified our understanding of leadership or identified gaps in research. Understanding leadership behavior is crucial for health care organizations considering AI because effective leadership shapes the strategic direction, adoption, and successful implementation of AI technologies.

Research Aim

To address this research gap and to establish a future research agenda this scoping review study aims to address two primary questions: (1) What role does leadership play in AI transformation within health care? and (2) What approaches can health care organizations use to empower their leaders in facilitating AI transformation?

Research Approach

This review follows scoping review methodology [ 30 ] to identify and analyze the current literature and report results following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews; Multimedia Appendix 1 ) guidelines [ 31 ].

Key Definitions

In the context of this study, AI refers to combination of machine learning algorithms, large language models, robotics, and natural language processing systems designed to mimic human cognitive functions, enabling machines to perform tasks autonomously or with minimal human intervention.

AI transformation refers to the systematic changes in clinical, operational, or organizational processes and business models due to the introduction of AI systems to optimize decision-making, automate tasks, improve patient outcomes, and drive organizational change. This involves identifying opportunities for AI-related innovation, integrating them into processes, and developing strategies to operationalize implementation while ensuring organizational readiness. This is essential for getting health care organizations AI-ready.

Further, in the context of this study, drawing from seminal management and leadership theories, we view leadership as an effective management practice [ 32 ]. However, we recognize that leadership roles in health care occur at the clinical, organizational, and systems levels of health systems. At the clinical level, leadership emerges through health care professionals who steer patient care and treatment decisions. At the organizational level, leadership involves middle managers such as unit heads and division leaders guiding health care institutions, administrative units, and personnel toward their goals. At the systems level, leadership encapsulates C-suite leadership responsible for navigating regulatory complexities and organizational and structural silos within complex health systems.

Eligibility Criteria

The following inclusion and exclusion criteria guided our study: (1) focused on AI in health care, (2) contained an evaluation of leadership, (3) were written in English, (4) were published in a peer-reviewed journal, (5) published between January 2015 and June 2023, and (6) used research.

Information Sources and Search Strategy

We adopted comprehensive search strategies for the following electronic databases focused on the health care and business literature: MEDLINE (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCO), Business Source Premier (via EBSCO), and Canadian Business & Current Affairs (via ProQuest). An academic librarian developed these search strategies with input from the research team. We initially conducted the search in Ovid MEDLINE. We then reviewed our search results using the Peer Review of Electronic Search Strategies tool [ 33 ], a checklist for comparing, among other things, the types of errors found in articles and the relative fit of articles to the research question before translating the search strategy into other databases using their command language. Our search was limited to articles published from January 2015 (from the first use of AI-powered chatbots in health care [ 34 ] to June 2023. We then ran searches in 4 databases and exported the final search results into the EndNote reference management software (Clarivate), and we removed duplicate articles manually. To capture any papers that may have been missed during the search process, we did forward and reverse citation searches of systematic review articles related to AI [ 35 ]. However, we did not find any additional articles that met our criteria. Finally, we imported search results to Covidence (Veritas Health Innovation), a review management software for abstract and title screening, full-text screening, and data charting.

Selection of Sources of Evidence and Data Charting

To minimize selection bias, 2 independent screeners reviewed the titles and abstracts of articles identified via the search against the eligibility criteria using Covidence. We identified articles that met the eligibility criteria for a comprehensive full-text screening. Two independent reviewers then evaluated the full texts against the eligibility criteria using Covidence. In discrepancies between the reviewers, a third reviewer served as the consensus reviewer and used Covidence to resolve conflicts between reviewer 1 and reviewer 2. Following the exclusion of irrelevant articles, we used a predefined data extraction form aligned with our research objectives and guiding questions for systematic data collection. Data extraction categories included data on study characteristics (eg, citations and country); methods (eg, aim, data collection methods, and methodological quality); study context (eg, leadership role, ie, clinical, organizational, or systems); leadership practices (ie, behavior, enablers, and barriers to leadership success); results (ie, main results and author conclusion); and an open-ended reviewer note (ie, capture any relevant information that might aid in the data analysis stage). The data abstraction form was piloted on a random sample of 4 included articles and modified based on feedback from the team. Full data abstraction began only after sufficient agreement had been obtained. Two reviewers independently extracted the data using Covidence, and a third reviewer assessed the data extraction for quality and consensus. Three authors then held a group discussion to resolve any conflicts.

Risk of Bias Assessment

The focus of scoping reviews is to provide a comprehensive overview of the available literature, identifying the extent, range, and nature of research on a particular topic rather than assessing the methodological quality of individual studies [ 35 ]. Therefore, we did not perform risk of bias evaluations on the articles included in compliance with the guidelines for scoping reviews.

Data Analysis and Synthesis

Our data analysis was guided by a thematic analysis process [ 36 ]. To ensure the accuracy of the emerging themes, we conducted our analysis collaboratively in reviewer pairs [ 35 ].

We initially analyzed the extracted data using an open-coding method guided by our research questions. Subsequently, we grouped the codes into categories based on the emerging patterns in the data, which we then synthesized into leadership functional domains, capacities, and context.

In the context of our analysis, functional domains refer to distinct areas of responsibility that a leader must effectively manage a task or a role. Capacity, on the other hand, pertains to the abilities—skills, competencies, or behaviors—that a leader must demonstrate to achieve desired goals. Context refers to the environment, conditions, and situational factors that shape and influence leadership practices and decisions.

Study Selection

As described in Figure 1 , the original searches generated 3541 articles published from January 2015 to June 2023. After removing 728 duplicate articles in EndNote, 2813 unique articles were uploaded to Covidence. A total of 2813 relevant studies were then screened using Covidence using the articles’ titles and abstracts. We determined that 97 articles met the criteria for a full-text review for eligibility screening. Within these 97 articles, 75 were excluded as they were opinion articles or commentaries without objective data. After conducting the full-text screening, we found that 22 articles met the final inclusion criteria.

Study Characteristics

Of the 22 studies identified for final inclusion in our review, 12 involved qualitative methods [ 37 - 48 ] such as interviews and case studies, whereas 4 studies involved mixed methods research [ 49 - 52 ] with a qualitative and quantitative strand. There were 3 narrative reports [ 53 - 55 ] based on document synthesis, and 3 studies involved quantitative methods [ 56 - 58 ] such as surveys. These articles focused on clinical, organizational, and systems leadership and came from Canada, China, Finland, Saudi Arabia, Sweden, the Netherlands, the United Kingdom, and the United States. The included papers addressed a broad array of AI applications in health care, including studies focused on improving workflows, quality of care, patient safety, resource optimization, and patient experience. From a clinical domain, researchers focused on primary care, health care systems, radiology, or global health. From a population perspective, the papers covered leadership from the perspective of primary care physicians, radiologists, nurses, nurse managers, public health professionals, global health professionals, health care entrepreneurs, and health care leaders. Table 1 provides a summary of study characteristics.

a N/A: not applicable.

Leadership Tasks Essential for AI Transformation in Health Care

We mapped the themes from the included studies across 4 functional domains of leadership task responsibility—technological (AI innovation), strategic (vision and alignment), operational (process and oversight), and organizational (culture and work environment).

The technological functional domain garnered the most significant attention in the literature. The core themes that emerged under the technological domain primarily focused on applying subject matter expertise and AI technical skills to effectively identify AI opportunities, as well as to foster an innovation mindset to develop, tailor, and seamlessly implement AI-driven solutions to address key AI opportunities within health care organizations.

Within the strategic functional domain, the literature underscored the importance of change management and communication as strategic tools for consensus and collaboration related to the AI transformation process. Another core theme that emerged focused on the critical importance of integrating AI solutions into the existing clinical care processes. This strategic alignment is essential for getting support from the staff and ensuring smooth operations of patient care outcomes while embracing the potential of AI solutions. Although the significance of talent strategy related to the recruitment and retention of AI technical expertise within organizations was mentioned, it was not widely seen across the included papers.

Table 2 provides a summary of how the technological and strategic functional domains map across the papers and provides key themes that emerged with the domain area.

Emerging evidence in the operational functional domain highlights leaders’ need to navigate ethical and risk management issues by establishing robust governance structures prioritizing patient data privacy and security while ethically integrating AI technologies within existing workflows. Additionally, the literature emphasizes that implementing AI in health care will require leaders to ensure new AI solutions comply with existing regulatory and control systems. The literature highlighted that leaders need to pay attention to process agility through continuous monitoring to ensure AI solutions can adapt to contextual changes.

Finally, the organizational functional domain emerges from the thematic analysis as a pivotal area for AI leadership. The literature emphasizes the importance of stakeholder engagement in building collaboration. Furthermore, it underscores the importance of decision makers’ sense-making to enhance their trust in AI opportunities and ensure that AI integration is supported by individuals across the organization. Further, the literature underscored the importance of organizational culture readiness to support physicians and nurses through protected time and incentive pay to engage, innovate, and adopt AI solutions. Table 3 provides a summary of how operational and organizational functional domains map across the papers.

Leadership Skills and Behaviors for Preparing Health Care Organizations for AI Transformation

We categorized the themes related to skills and behaviors into 3 essential capacities that a leader must demonstrate to achieve desired goals—technical capacity, adaptive capacity, and interpersonal capacity. Technical capacity encompasses (1) AI literacy, (2) subject matter knowledge, (3) change leadership skills, and (4) innovation mindset to identify AI innovation opportunities. The interpersonal capacity involves several vital facets such as (1) the ability to foster partnerships among diverse stakeholders, (2) the ability to comprehend diverse stakeholder perspectives and deftly influence adoption, (3) the ability to build trust and collaboration, (4) self-awareness and humility to assemble teams with complementary skills, and (5) the integrity and accountability to embody ethical principles. The adaptive capacity encompasses (1) the foresight and sense-making abilities to discern emerging technologies and their implications within the health care sphere; (2) the agility to identify and capitalize on transformative opportunities, swiftly adapting and aligning strategies with evolving contexts; and (3) systems thinking to enable an understanding of how elements interconnect and how changes in 1 area can reverberate throughout the entire system.

Contextual Factors Influencing Leadership in AI Transformation

The emerging themes from our review reveal that dynamic environmental and situational factors, including regulatory, technology, and organizational contexts, shape AI transformation within health care organizations. For instance, the regulatory context and frameworks related to health professions and health care organizations play a critical role in how AI can be integrated within the organizations. Similarly, the technology context such as the availability of AI technical talent, the retention of technical expertise, the dynamic nature of AI maturity, and the presence of incentives and technological resources for AI innovation or adoption will significantly influence a leader’s ability to effectively drive AI readiness. Finally, the organization context is a critical influence on leaders’ capacity for AI adoption and implementation. Organizations that promote and reward innovation and that have transparent communication practices shape leaders’ ability to pursue AI opportunities.

Strategies for Empowering Health Care Leaders to Facilitate AI Transformation

For the technological domain, the included papers discussed approaches such as upskilling clinical experts with the necessary AI technical skills and ensuring the presence of specialized experts, such as computer scientists, to enable the subject matter experts to develop, test, and seamlessly integrate AI solutions. Further, the papers discussed collaborative strategies such as clinicians and computer scientists working together to effectively identify AI opportunities and develop, adopt, and implement AI solutions in clinical or operational areas.

For the strategic domain, organizational support was essential in supporting leaders to assess and identify AI opportunities that strategically align with organizational priorities and develop strategies to ensure AI transformation garners support from key stakeholders within the complex regulatory and environmental contexts. The literature also highlighted the competition for AI talent in health care and emphasized the significance of talent retention strategies to preserve the organization’s AI technical expertise.

Then, in the operational domain, the emphasis was on establishing governance structures to continuously monitor data quality, patient privacy, and patient care experiences and assess the feasibility and financial implications of AI transformation. These governance structures ensure effective oversight and management of AI initiatives within health care organizations.

Finally, for the organizational domain, the focus was on the pivotal role of organizational culture in AI leadership. Leaders require organizational support to cultivate an environment that fosters innovation and actively incentivizes clinical leaders, such as physicians and nurses, through protected time and incentive pay to innovate and adopt AI solutions. Transparent decision-making processes related to AI solutions are essential cultural elements that build trust in AI systems and promote collaboration among the diverse stakeholders involved in AI transformation within health care organizations.

Principal Findings

The purpose of a scoping review is not to draw definitive conclusions but to map the literature, identify emerging patterns, and develop critical propositions. As described in Figure 2 , analysis of current literature shows that leading organizations toward AI transformation requires multidimensional leadership. As such, health care organizations need to engage leaders in the technological, strategic, operational, and organizational domains to facilitate AI transformation in their organizations. Further, the reviewed papers suggest that individuals in AI-related leadership roles need to demonstrate (1) technical capacity to understand the technology and innovation opportunities, (2) adaptive capacity to respond to contextual changes, and (3) interpersonal capacity to navigate the human aspects of the AI transformation process effectively. Furthermore, our study illuminates that leaders in the AI-related leadership roles need to navigate regulatory context, the dynamic nature of changing technology context, and organization context.

Prior Research

Health care organizations are marked by multifaceted interdependencies among medical facilities, health care providers, patients, administrative units, technology, and the regulatory environment. Therefore, the leadership required for AI transformation—which includes identifying AI opportunities, implementing AI solutions, and achieving full-scale AI adaptation—is not a static role but a continuous and dynamic process. Effective leadership involves the capacity to continuously identify opportunities for AI transformation, influence the thoughts and actions of others, and navigate the complex dynamics of the health care setting and AI technology landscape simultaneously. However, the current literature has not fully articulated this multidimensionality, often focusing on leadership through a linear approach.

Further, multiple situational factors can shape AI transformation. First, the rapid growth of AI technologies introduces an element of uncertainty, making it challenging to anticipate the long-term impact and sustainability of specific AI solutions [ 6 ]. Second, AI implementation involves many stakeholders, from technical experts and domain specialists to clinicians, administrators, patients, vendors, and regulatory bodies. Each stakeholder group brings its unique perspectives, priorities, and control systems into the equation, necessitating leaders to navigate competing values, trade-offs, and paradoxes [ 27 ]. Third, once alignment is achieved, the integration of AI within an organization triggers a need for a cultural shift, altering work practices and decision-making processes [ 38 , 59 ]. Fourth, the effectiveness of AI solutions hinges on the availability of high-quality data for informed insights and decision-making. When implementing solutions originally developed within different contexts, local organizations must ensure data integrity and the solution’s adaptability to the organization’s unique context [ 18 ]. This challenge is compounded by emerging regulatory frameworks, which add a layer of complexity. Ensuring compliance and the responsible use of AI technologies has become a critical consideration [ 29 , 50 , 60 ]. Finally, introducing AI may provoke resistance from employees concerned about job displacement or disruptions to established workflows. This problem is further compounded when an organization transitions toward integrating multiple AI systems, as these changes can lead to periods of chaos and confusion [ 59 ].

Emerging key opinions and evidence from outside the health domain indicate that leaders must possess an understanding of data quality nuances, assess process risks, and manage AI as a new team member. Additionally, leaders should have a firm grasp of technology, articulate clear business objectives, define precise goals, uphold a long-term vision, prepare their teams for AI transformation, manage data resources effectively, and foster organizational collaboration [ 3 , 61 - 67 ].

Our findings on the leadership required for AI transformation in health care organizations reinforce this multidimensionality of leadership to effectively navigate the complexities of AI transformation and successfully leverage its potential to drive transformative change. Leaders must operate across different functional domains—technological, strategic, operational, and organizational—while demonstrating technical, adaptive, and interpersonal capacities.

Further, our findings show contingency leadership theories, complexity theory, and transformational leadership theory as relevant theoretical domains for further explaining the different facets of leadership behaviors needed to navigate the multidimensionality of leadership required for AI transformation.

Contingency theories suggest that leadership effectiveness depends on situational factors, which should be considered in future AI implementation studies in the context of AI adaptation and integration within health care organizations [ 68 , 69 ]. Complexity theory provides a framework for examining leadership behaviors in interconnected, dynamic environments where leaders must balance innovation and stability and demonstrate an adaptive approach to challenges, characterized by uncertainty and change [ 70 - 73 ]. Transformational leadership theory emphasizes motivating, empowering, and developing others by fostering trust and collaboration while challenging the status quo to drive organizational change and innovation [ 74 , 75 ]. These theories should be considered in future AI implementation studies within health care organizations.

Future research and training programs related to AI in health care should examine the leadership required for AI transformation through the lens of multidimensionality, providing insights into the interrelatedness of functional domains, leadership capacities, and contextual enablers and barriers, while exploring the key theoretical domains related to contingency, complexity, and transformational leadership to further understand the interpersonal dynamics shaping AI transformation in health care.

Limitations

Some limitations to our scoping review are worth noting. First, given the contextual variability in the included studies and the methodological variations, we could not establish firm correlations about specific leadership domains, capacities, and contextual factors; the effectiveness of leadership approaches; or the moderating effects of contextual factors. Consequently, we have presented only the overarching emergent themes.

Second, our study is limited by the significant variation in conceptual definitions of leadership and leadership competencies found in the current literature, which often lacks more standardized definitions or instruments for measurement. This variation caused conceptual inconsistencies. We addressed the inconsistencies by clearly defining what constitutes a functional domain, capacity, and context before our data analysis to address this. We iteratively coded the data into themes to ensure all relevant aspects were captured.

Third, our search strategy focused on MEDLINE-indexed journals, which may exclude some newer journals indexed in PubMed but not yet in MEDLINE. While this might limit the capture of the very latest advancements in digital health, it does not diminish the robustness of the review. Fourth, we retrieved only articles written in English, which possibly limited the comprehensiveness of our findings. Fifth, we looked at AI as a system and did not look at the relationship between the implementation of different types of AI tools and leadership behaviors which was beyond the scope of our review. Finally, our analysis used an inductive approach and was not informed by a predetermined theory to aid the mapping of the literature. This may have limited our analysis in capturing different elements of an umbrella theory.

Recommendations for Future Design and Research

Leading organizations toward AI transformation is an adaptive challenge influenced by a myriad of interwoven situational factors that create a dynamic and intricate environment. The body of literature related to AI in health care is rapidly expanding, and the recommendations imparted by this review, alongside the multidimensional leadership framework ( Figure 2 ), stand poised to guide research and practice to empower health care organizations in their AI transformation journey. Future research on AI transformation, which includes innovation identification, implementation, and scaling, can use this framework to understand the role of leadership in driving successful outcomes.

Further, future research must undergo methodological expansion by embracing qualitative and mixed methods approaches to illuminate the intricate temporal aspects of AI transformation and corresponding evolving leadership behaviors.

Conclusions

In summary, emerging evidence shows that multidimensional leadership plays crucial role in AI transformation in health care organization. Leaders must adeptly balance technology opportunities while demonstrating unwavering empathy for stakeholder needs and nimble adaptability to accommodating the ever-changing contextual landscape, which encompasses the regulatory frameworks, the evolution of technology, and the organization’s priorities.

Acknowledgments

This work is supported through a grant from the University of Toronto’s Connaught Global Challenges. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the study.

Data Availability

The main study data are the data extraction materials and quality ratings of included papers, most of which are included in the study tables. The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

All authors were involved in conception and design of the study and approved the protocol. AS and NS were responsible for overseeing the search of databases and literature. AS, NS, and SS were involved in the screening of articles, data extraction and data verification, and analysis of data. All authors were involved in data interpretation, supported in the drafting of the paper, which was led by AS, and all authors supported in revising and formatting of the paper. All authors have provided final approval of the version of the paper submitted for publication, and all authors agree to be accountable for all aspects of the work.

Conflicts of Interest

None declared.

Updated PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist.

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Abbreviations

Edited by T de Azevedo Cardoso, G Eysenbach; submitted 14.11.23; peer-reviewed by D Chrimes, TAR Sure, S Kommireddy, J Konopik, M Brommeyer; comments to author 20.02.24; revised version received 12.03.24; accepted 15.07.24; published 14.08.24.

©Abi Sriharan, Nigar Sekercioglu, Cheryl Mitchell, Senthujan Senkaiahliyan, Attila Hertelendy, Tracy Porter, Jane Banaszak-Holl. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.08.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

Intrapersonal Utility Comparisons as Interpersonal Utility Comparisons: Welfare, Ambiguity, and Robustness in Behavioral Policy Problems

We consider the optimal policy problem of a benevolent planner, who is uncertain about an individual's true preferences because of inconsistencies in revealed preferences across behavioral frames. We adapt theories of expected utility maximization and ambiguity aversion to characterize the planner's objective, which results in welfarist criteria similar to social welfare functions, with intrapersonal frames replacing interpersonal types. Under paternalistic risk aversion or ambiguity aversion, a policy is less desirable to the planner, holding all else fixed, when it leads to more disagreement about welfare from revealed preferences. We map some examples of behavioral models into our framework and describe how this notion of robustness plays out in applied settings.

For valuable discussions and comments, we thank Scott Elliott, Jacob Goldin, Louis Kaplow, Ben Lockwood, Yusufcan Masatlioglu, Emel Filiz-Ozbay, Alex Rees-Jones, Joel Slemrod, Luminita Stevens, and Dmitry Taubinsky. Canishk thankfully acknowledges financial support from the Economic and Social Research Council DTP [Grant No: ES/P000622/1]. The authors have no relevant material financial or other interests that relate to this research paper. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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How to Write a Research Proposal: (with Examples & Templates)

Table of Contents

Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

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Get accurate academic translations, rewriting support, grammar checks, vocabulary suggestions, and generative AI assistance that delivers human precision at machine speed. Try for free or upgrade to Paperpal Prime starting at US$19 a month to access premium features, including consistency, plagiarism, and 30+ submission readiness checks to help you succeed.  

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