This systematic review of time management research was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Page et al., 2021; see Figure 1). We searched PsycINFO, ERIC, ProQuest Dissertations and Theses, and Google Scholar using combinations of the following terms: time management, time allocation, time structuring, and time use. Additional sources were identified through reference list screening. We developed the search strategy collaboratively and piloted it to ensure comprehensive coverage across databases. Search terms were iteratively refined to minimize bias in study retrieval. The search yielded 5,098 records. We focused specifically on dissertations and peer-reviewed journal articles published in English. Extending the review by Claessens et al. (2007), we included journal articles published between 2006 and 2021. Because dissertations were not addressed in earlier reviews, we included all dissertations up to the end of 2021. This timeframe also captures the period prior to the COVID-19 pandemic, which significantly disrupted daily life and altered individuals' perceptions and management of time (e.g., Ding et al., 2024; Forstervold et al., 2022), with a time lag to allow for publication of this work.

Two authors independently screened all titles, abstracts, and full texts based on predefined inclusion criteria. Included studies were peer-reviewed journal articles or dissertations written in English and published in or before 2021 with no restriction on study type or research design. We excluded studies not situated in higher education or work contexts (e.g., primary/secondary education, informal learning environments or leisure time). Studies that did not examine and report findings on individual time management were also excluded, e.g., studies focusing on collaborative time management.

To assess the methodological quality of included studies, we used the Mixed Methods Appraisal Tool (MMAT; Hong et al., 2018), which is designed to evaluate a wide range of empirical research, including qualitative, quantitative (randomized, non-randomized, and descriptive), and mixed-methods studies. The MMAT includes two initial screening questions and five criteria specific to each study type. We selected MMAT due to its flexibility in appraising diverse designs within a single review. In line with the developers' guidance, we did not compute overall scores. Instead, we presented the criteria ratings and summarized key quality concerns. A detailed MMAT rating matrix is provided in Supplementary Table S1.

Inter-rater reliability was calculated on 20% of records at each screening phase, showing substantial agreement for title and abstract screening (κ = 0.76) and full-text screening (κ = 0.79). Discrepancies were resolved through discussion, with a third author adjudicating when needed. The same process was used during data extraction: one author extracted data using a standardized form, and a second verified a random subset. Any disagreements were discussed and, if unresolved, referred to the third author. These procedures enhanced transparency and minimized bias.

The systematic review identified 107 relevant sources (86 peer-reviewed articles and 21 dissertations). Of these, 69 focused on higher education, 36 on workplace settings, and 2 addressed both contexts. Our sample includes a total sample size of 32,959, including 24,068 students in higher education and 8891 workforce professionals. These sources investigated time management in educational and work settings using diverse quantitative, qualitative, and mixed-method designs. See Supplementary Table S2 for characteristics of each included study.

Of the included studies, the quality assessment showed that 41 met all five quality criteria. Forty-five studies lacked sufficient information to assess at least one criterion, preventing a clear judgment. Nineteen studies failed to meet one criterion, three studies did not meet two, and one study failed to meet three of the five criteria. The most common concerns involved the sampling process in quantitative descriptive studies (n = 11), risk of non-response bias (n = 4), and the representativeness of samples in non-randomized trials (n = 3). See Supplementary Table S1 for full quality appraisal details.

Thematic analysis (Thomas and Harden, 2008) was used to ensure transparency and identify themes related to the research questions. Definitions and findings were coded line-by-line, generating a codebook to compare codes across studies systematically. Codes were analyzed for underlying meanings and grouped into related categories, which were further refined into higher-level constructs and overarching themes. This iterative process facilitated a comprehensive understanding of time management.

Thematic analysis of the included studies identified six overarching themes that structured the synthesis of findings. These themes reflect recurring patterns in how time management is conceptualized, studied, and applied across contexts. First, definitions of time management varied widely, ranging from a narrow focus on productivity behaviors to broader interpretations involving self-regulation and multidimensional processes. Second, common behavioral strategies emerged, including goal setting, prioritization, planning, and scheduling, often adapted to specific academic or professional settings. Third, individual differences such as personality traits (e.g., conscientiousness), self-regulated learning skills, and motivational factors were frequently reported as influencing time management practices. Fourth, studies linked time management to a range of outcomes, including academic achievement, job performance, wellbeing, and reduced stress, though effect sizes and consistency varied. Fifth, contextual and cultural influences were increasingly recognized, highlighting how environmental factors and even task characteristics shape time management practices. Finally, intervention studies suggested that time management skills can be improved through training, although evidence for long-term behavioral change remains limited. These themes informed the organization and interpretation of findings presented in the results section.

These six themes directly address the review's research questions by offering a structured synthesis of how time management is both conceptualized and operationalized. Themes related to varying definitions of time management respond to Research Question 1 by illustrating the conceptual diversity across studies, from narrow behavioral models to comprehensive self-regulatory frameworks. Themes involving behavioral strategies, individual differences, contextual influences, outcomes, and interventions collectively inform Research Question 2, revealing how time management practices are employed and how they influence performance, wellbeing, and stress among students and employees. This thematic organization enhances the review's contribution by aligning empirical patterns with the conceptual aims of the research.

While the quality appraisal informed our analytic perspective, we did not observe consistent patterns linking study quality to the themes or findings that emerged. Regardless of methodological rigor, studies contributed meaningfully to the synthesis, suggesting that the identified themes reflect robust trends across diverse research contexts.

Time management lacks a universal definition. Since dissertations often present overviews rather than a single conceptual definition, we analyzed the 86 articles.

Most articles (24 out of 86) used or adapted Claessens et al.'s (2007) conceptualization, which views time as a limited resource, with key actions including goal setting, prioritizing, planning, and self-assessing time use. Work studies emphasized efficient planning to boost productivity, but monitoring progress was less emphasized.

Macan et al. (1990) and Macan (1994) proposed another widely used framework, categorizing time management behavior into goal-setting and prioritization, scheduling and planning, organizing, and perceived control over time. Fifteen studies in our sample (7 in education, 8 in work) used this model. Five articles focused on the objectives of time management, defining it as efficient time allocation to enhance productivity (e.g., Crnjar et al., 2019).

Forty-two articles lacked a clear conceptual definition of time management, with many offering no (n = 30), multiple (n = 6), or merely operational definitions (n = 6). Of operational definitions, surveys were the most common method, followed by interviews, diaries, and trace data (see Table 1).

The most used surveys were the Time Management Behavior Scale (TMBS; Macan et al., 1990; Macan, 1994) in 39 studies and the Time Management Questionnaire (TMQ; Britton and Tesser, 1991) in 25 studies (see Table 2). Both showed high reliability, with Cronbach's alpha ranging from 0.76–0.97 for the TMBS (e.g., Douglas et al., 2016; Wolters et al., 2017) and 0.75–0.88 for the TMQ (e.g., Ghiasvand et al., 2017; Gravley, 2020).

Twenty-two surveys, mostly self-developed, some outdated (e.g., “managing postal correspondence”) (Macan et al., 1990), were each used in one study. Diaries were employed in five work-based studies as interventions and data collection tools, tracking planning, task completion, time management strategies, and multitasking over 2–5 weeks (Claessens, 2004; Häfner et al., 2014a; Kirchberg et al., 2015).

Seven studies involved interviews with students (n = 3) and employees (n = 4) about time management strategies. Student interviews focused on first-year university students (Van der Meer et al., 2010), nursing students (Mirzaei et al., 2012), and ESL college students (Liu, 2019). Workplace studies explored tools and strategies used by program designers (Wajcman, 2019), managers, school administrators (Naparan and Tulod, 2021; Wong and Waldner, 2021) and employees across sectors (Claessens, 2004).

Five studies utilized trace data, including 7-day time logs (Hensley et al., 2018) and software tracking work activities (Pammer and Bratic, 2013). Other research analyzed task completion during simulations (DiGregorio, 2020) and students' learning management system engagement, focusing on behaviors such as studying on time, ahead, or catching up (Ahmad Uzir et al., 2020; Li et al., 2020). These studies emphasized task timing and behavioral indicators of time management.

Researchers investigated how time management can be facilitated through training (n = 26) and its association with individual differences (n = 25), wellbeing (n = 26), performance (n = 22), motivation (n = 14), procrastination (n = 10), task characteristics (n = 8), and learning strategies (n = 6). See Table 3 for key findings and best practices.

Definitions of time management vary widely, encompassing processes such as goal setting and planning, as well as broader aims like enhancing productivity. However, many studies fail to offer clear or consistent definitions, making it difficult to generalize findings across contexts (Claessens et al., 2007). A clear conceptualization of time management is essential for advancing research and practice in both higher education and professional learning environments. Drawing on the work of Aeon and Aguinis (2017), Aeon et al. (2021), we define time management as the allocation of time toward goal achievement through organization and adaptation. This definition emphasizes the role of metacognitive monitoring in adjusting strategies to meet goals effectively (Claessens et al., 2007; Wolters and Brady, 2021).

Sardinha et al.'s (2020) flexible time management model also integrates self-awareness—a key metacognitive component—with time management and temporal perspectives. Temporal orientation shapes—and is shaped by—time-related behaviors (Keough et al., 1999; Holman and Zimbardo, 2009), offering insight into individual differences in how time management is understood and supported (Sardinha et al., 2021a,b, 2023).

Time management is typically assessed through interviews, diaries, and survey instruments such as the Time Management Questionnaire (TMQ; Britton and Tesser, 1991) and the Time Management Behavior Scale (TMBS; Macan et al., 1990), which are often adapted or abbreviated in subsequent research (Parke et al., 2018; Zampetakis et al., 2010). The variability in definitions and measurement approaches presents challenges for comparing findings and for designing effective time management interventions within higher education and the workplace.

To capture the multifaceted nature of time management, we examined how different strategies impact individuals in both higher education and professional contexts. Our findings contribute to a growing body of research on self-regulated learning and time use by highlighting the nuanced ways in which individual differences and strategic behaviors shape outcomes related to academic and professional functioning.

Individual differences. In line with Aeon et al. (2021), we found a weak gender effect favoring women, who tended to report greater adaptability and control over their time. While consistent with previous findings, this result should be interpreted cautiously, as gender was measured dichotomously. More inclusive and multidimensional approaches to studying gender may provide richer insight into how time management manifests across populations. Age-related patterns also emerged, with younger individuals more likely to engage in short-term planning and older individuals demonstrating stronger goal-setting skills. These findings suggest that time management evolves over time and with experience, though further longitudinal research is needed. Additionally, personality traits—particularly conscientiousness, openness, and extraversion—were positively associated with time management, aligning with earlier research (Claessens et al., 2007; Aeon et al., 2021). These traits may underpin individual propensities to engage in organized, goal-directed behaviors, which are beneficial in both academic and professional contexts.

Productivity. Our findings support prior evidence that time management is positively associated with productivity and academic achievement (Aeon et al., 2021). Goal-setting, prioritization, and both short- and long-term planning consistently predicted higher performance. This aligns with Ahmady et al. (2021), who found that effective time management among medical students led to increased academic achievement. Similarly, Bedi and Sass (2023), in a meta-analysis of workforce professionals, reported that time management significantly enhances work productivity. These converging findings highlight the importance of supporting time management development in higher education, not only to enhance student performance but also to prepare learners for productive engagement in professional environments.

Wellbeing. Time management also contributes meaningfully to wellbeing. Aeon et al. (2021) found a moderate positive link between time management and wellbeing, which our study confirms. Planning, goal-setting, and scheduling reduce stress, burnout, and depression, thereby improving mental health and satisfaction with academic or professional responsibilities (Claessens et al., 2007). These findings are further supported by Ahmady et al. (2021), who showed that time management among medical students significantly reduced stress. Additionally, Bedi and Sass (2023) found that time management is associated with greater job satisfaction among professionals. Together, these findings emphasize the role of time management as a key factor not only in performance, but also in sustaining mental health, emotional resilience, and satisfaction—critical components of success in both academic and professional settings.

Motivation. Consistent with Aeon et al. (2021), our findings indicate that time management and motivation are closely linked. Individuals who manage their time effectively tend to feel more competent and engaged, and place greater value on their tasks. These motivational benefits are likely reinforced through strategic behaviors like scheduling, prioritization, and goal-setting, which can help individuals experience a sense of control and progress—key drivers of intrinsic motivation. In higher education, supporting students' time management skills may thus serve as a pathway to improved engagement and persistence.

Procrastination and learning. Our study also aligns with Wolters and Brady's (2021) self-regulated learning framework, highlighting the role of time management in reducing procrastination and enhancing metacognitive and cognitive learning strategies. By fostering skills such as task organization and scheduling, educators can help students not only manage their time more effectively but also engage more deeply in learning processes that are essential for academic success.

Training. Like Claessens et al. (2007), we found that time management training can enhance individuals' wellbeing and sense of control while boosting productivity. Programs that incorporate explicit instruction in goal-setting, prioritization, and planning appear especially promising. However, our findings also highlight variability in outcomes based on differences in training design and delivery. Future research should explore how time management interventions can be tailored to different populations and educational contexts, with attention to intensity, content, and integration into existing curricula.

Overall, our findings suggest that time management is a critical skill that supports performance, wellbeing, motivation, and learning in both academic and professional settings. For educators, researchers, organizational leaders, and professional development practitioners, this underscores the importance of developing evidence-based strategies for supporting time management across contexts. Future work should continue to explore how these strategies can be embedded within educational curricula and co-curricular initiatives, as well as within workplace training and professional development programs, and how they can be adapted to meet the needs of diverse learners and professionals across developmental and contextual boundaries.