Principles and Practice of Structural Equation Modeling

Assessing measurement model quality in PLS-SEM using confirmatory composite analysis

Hair, J. F., Howard, M. C., & Nitzl, C. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2019.11.069 · Cited by 5,446

POSITIVE PSYCHOLOGICAL CAPITAL: MEASUREMENT AND RELATIONSHIP WITH PERFORMANCE AND SATISFACTION

LUTHANS, F., AVOLIO, B. J., AVEY, J. B., & NORMAN, S. M. (2007) · Personnel Psychology · doi:10.1111/j.1744-6570.2007.00083.x · Cited by 4,809

Measurement invariance conventions and reporting: The state of the art and future directions for psychological research

Putnick, D. L., & Bornstein, M. H. (2016) · Developmental Review · doi:10.1016/j.dr.2016.06.004 · Cited by 4,369

Scale Development Research: A Content Analysis and Recommendations for Best Practices

Worthington, R. L., & Whittaker, T. A. (2006) · The Counseling Psychologist · doi:10.1177/0011000006288127 · Cited by 4,087

Preliminary Psychometric Properties of the Acceptance and Action Questionnaire–II: A Revised Measure of Psychological Inflexibility and Experiential Avoidance

Bond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., Waltz, T., & Zettle, R. D. (2011) · Behavior Therapy · doi:10.1016/j.beth.2011.03.007 · Cited by 3,950

Development and validation of the short grit scale (grit-s)

Duckworth, A. L., & Quinn, P. D. (2009) · Journal of Personality Assessment · doi:10.1080/00223890802634290 · Cited by 3,376

Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares

Li, C.-H. (2016) · Behavior Research Methods · doi:10.3758/s13428-015-0619-7 · Cited by 3,031

Consistent Partial Least Squares Path Modeling1

Dijkstra, T. K., & Henseler, J. (2015) · MIS Quarterly · doi:10.25300/misq/2015/39.2.02 · Cited by 2,898

Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: guidelines using an applied example

Hair, J., & Alamer, A. (2022) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2022.100027 · Cited by 2,833

A Brief Guide to Structural Equation Modeling

Weston, R., & Gore, P. A. (2006) · The Counseling Psychologist · doi:10.1177/0011000006286345 · Cited by 2,718

Basic psychological need satisfaction, need frustration, and need strength across four cultures

Chen, B., Vansteenkiste, M., Beyers, W., Boone, L., Deci, E. L., Van der Kaap-Deeder, J., Duriez, B., Lens, W., Matos, L., Mouratidis, A., et al. (2015) · Motivation and Emotion · doi:10.1007/s11031-014-9450-1 · Cited by 2,507

The Mini-IPIP Scales: Tiny-yet-effective measures of the Big Five Factors of Personality.

Donnellan, M. B., Oswald, F. L., Baird, B. M., & Lucas, R. E. (2006) · Psychological Assessment · doi:10.1037/1040-3590.18.2.192 · Cited by 2,442

Un sistema de clasificación de los diseños de investigación en psicología

Ato, M., López-García, J. J., & Benavente, A. (2013) · Anales de Psicología · doi:10.6018/analesps.29.3.178511 · Cited by 2,254

Exploratory Factor Analysis: A Guide to Best Practice

Watkins, M. W. (2018) · Journal of Black Psychology · doi:10.1177/0095798418771807 · Cited by 2,218

Latent class analysis: a guide to best practice

Weller, B. E., Bowen, N. K., & Faubert, S. J. (2020) · Journal of Black Psychology · doi:10.1177/0095798420930932 · Cited by 2,223

Predicting green product consumption using theory of planned behavior and reasoned action

Paul, J., Modi, A., & Patel, J. (2016) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2015.11.006 · Cited by 2,399

Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024) · Asia Pacific Journal of Management · doi:10.1007/s10490-023-09871-y · Cited by 2,262

A checklist for testing measurement invariance

van de Schoot, R., Lugtig, P., & Hox, J. (2012) · European Journal of Developmental Psychology · doi:10.1080/17405629.2012.686740 · Cited by 2,064

The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education

Scherer, R., Siddiq, F., & Tondeur, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2018.09.009 · Cited by 1,923

Young consumers' intention towards buying green products in a developing nation: Extending the theory of planned behavior

Yadav, R., & Pathak, G. S. (2016) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.06.120 · Cited by 1,463

Determinants of consumers’ green purchase behavior in a developing nation: applying and extending the theory of planned behavior

Yadav, R., & Pathak, G. S. (2017) · Ecological Economics · doi:10.1016/j.ecolecon.2016.12.019 · Cited by 1,318

An Updated Guideline for Assessing Discriminant Validity

Rönkkö, M., & Cho, E. (2022) · Organizational Research Methods · doi:10.1177/1094428120968614 · Cited by 1,309

Why employees do bad things: Moral disengagement and unethical organizational behavior

MOORE, C., DETERT, J. R., KLEBE TREVIÑO, L., BAKER, V. L., & MAYER, D. M. (2012) · Personnel Psychology · doi:10.1111/j.1744-6570.2011.01237.x · Cited by 1,159

Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model

Hoque, R., & Sorwar, G. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.02.002 · Cited by 1,004

An investigation of mobile learning readiness in higher education based on the theory of planned behavior

Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.04.015 · Cited by 1,057

Modelling technology acceptance in education: A study of pre-service teachers

Teo, T. (2009) · Computers & Education · doi:10.1016/j.compedu.2008.08.006 · Cited by 1,009

Developing and validating a service robot integration willingness scale

Lu, L., Cai, R., & Gursoy, D. (2019) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2019.01.005 · Cited by 1,013

The Impact of Leadership on Student Outcomes: How Successful School Leaders Use Transformational and Instructional Strategies to Make a Difference

Day, C., Gu, Q., & Sammons, P. (2016) · Educational Administration Quarterly · doi:10.1177/0013161x15616863 · Cited by 996

Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale

Wang, B., Rau, P.-L. P., & Yuan, T. (2023) · Behaviour & Information Technology · doi:10.1080/0144929x.2022.2072768 · Cited by 1,036

What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM

Filieri, R. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2014.11.006 · Cited by 1,083

Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education

Celik, I. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107468 · Cited by 1,012

Motivation in online learning: testing a model of self-determination theory

Chen, K.-C., & Jang, S.-J. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.01.011 · Cited by 955

Adaptation of the Fear of COVID-19 Scale: Its Association with Psychological Distress and Life Satisfaction in Turkey

Satici, B., Gocet-Tekin, E., Deniz, M. E., & Satici, S. A. (2021) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-020-00294-0 · Cited by 922

Understanding the relationships between tourists’ emotional experiences, perceived overall image, satisfaction, and intention to recommend

Prayag, G., Hosany, S., Muskat, B., & Del Chiappa, G. (2017) · Journal of Travel Research · doi:10.1177/0047287515620567 · Cited by 924

Factors influencing teachers’ intention to use technology: Model development and test

Teo, T. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.06.008 · Cited by 914

Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth

Filieri, R., Alguezaui, S., & McLeay, F. (2015) · Tourism Management · doi:10.1016/j.tourman.2015.05.007 · Cited by 882

Green purchasing behaviour: A conceptual framework and empirical investigation of Indian consumers

Jaiswal, D., & Kant, R. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2017.11.008 · Cited by 846

A self-determination theory approach to predicting school achievement over time: the unique role of intrinsic motivation

Taylor, G., Jungert, T., Mageau, G. A., Schattke, K., Dedic, H., Rosenfield, S., & Koestner, R. (2014) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2014.08.002 · Cited by 816

A comparative study of cb-sem and pls-sem for theory development in family firm research

Astrachan, C. B., Patel, V. K., & Wanzenried, G. (2014) · Journal of Family Business Strategy · doi:10.1016/j.jfbs.2013.12.002 · Cited by 766

Evidence for proposed ICD-11 PTSD and complex PTSD: a latent profile analysis

Cloitre, M., Garvert, D. W., Brewin, C. R., Bryant, R. A., & Maercker, A. (2013) · European Journal of Psychotraumatology · doi:10.3402/ejpt.v4i0.20706 · Cited by 751

The impact of website quality on customer satisfaction and purchase intentions: Evidence from Chinese online visitors

Bai, B., Law, R., & Wen, I. (2008) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2007.10.008 · Cited by 749

Development and Validation of a Self-Report Measure of Mentalizing: The Reflective Functioning Questionnaire

Fonagy, P., Luyten, P., Moulton-Perkins, A., Lee, Y.-W., Warren, F., Howard, S., Ghinai, R., Fearon, P., & Lowyck, B. (2016) · PLOS ONE · doi:10.1371/journal.pone.0158678 · Cited by 754

Do perceived autonomy-supportive and controlling teaching relate to physical education students' motivational experiences through unique pathways? Distinguishing between the bright and dark side of motivation

Haerens, L., Aelterman, N., Vansteenkiste, M., Soenens, B., & Van Petegem, S. (2015) · Psychology of Sport and Exercise · doi:10.1016/j.psychsport.2014.08.013 · Cited by 747

A multidimensional approach to measuring well-being in students: Application of the PERMA framework

Kern, M. L., Waters, L. E., Adler, A., & White, M. A. (2015) · The Journal of Positive Psychology · doi:10.1080/17439760.2014.936962 · Cited by 743

The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards ‘untact’ tourism in South Korea during the first wave of the pandemic (March 2020)

Bae, S. Y., & Chang, P.-J. (2021) · Current Issues in Tourism · doi:10.1080/13683500.2020.1798895 · Cited by 743

Science Motivation Questionnaire II: Validation with Science Majors and Nonscience Majors

Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011) · Journal of Research in Science Teaching · doi:10.1002/tea.20442 · Cited by 733

Dimensions of Reading Motivation and Their Relation to Reading Behavior and Competence

Schiefele, U., Schaffner, E., Möller, J., & Wigfield, A. (2012) · Reading Research Quarterly · doi:10.1002/rrq.030 · Cited by 694

The curiosity and exploration inventory-II: Development, factor structure, and psychometrics

Kashdan, T. B., Gallagher, M. W., Silvia, P. J., Winterstein, B. P., Breen, W. E., Terhar, D., & Steger, M. F. (2009) · Journal of Research in Personality · doi:10.1016/j.jrp.2009.04.011 · Cited by 674

The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence

Kaya, F., Aydin, F., Schepman, A., Rodway, P., Yetişensoy, O., & Demir Kaya, M. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2151730 · Cited by 688

Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study

Gustavson, K., von Soest, T., Karevold, E., & Røysamb, E. (2012) · BMC Public Health · doi:10.1186/1471-2458-12-918 · Cited by 679

What drives purchase intention for paid mobile apps? An expectation confirmation model with perceived value

Hsu, C.-L., & Lin, J. C.-C. (2015) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2014.11.003 · Cited by 662

Adoption of artificial intelligence in higher education: A quantitative analysis using structural equation modelling

Chatterjee, S., & Bhattacharjee, K. K. (2020) · Education and Information Technologies · doi:10.1007/s10639-020-10159-7 · Cited by 747

Developmental changes in executive functioning.

Lee, K., Bull, R., & Ho, R. M. H. (2013) · Child Development · doi:10.1111/cdev.12096 · Cited by 633

Touch your toes! Developing a direct measure of behavioral regulation in early childhood.

Cameron Ponitz, C. E., McClelland, M. M., Jewkes, A. M., Connor, C. M., Farris, C. L., & Morrison, F. J. (2008) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2007.01.004 · Cited by 635

Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19

Gopal, R., Singh, V., & Aggarwal, A. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10523-1 · Cited by 618

Examining branding co-creation in brand communities on social media: Applying the paradigm of Stimulus-Organism-Response

Kamboj, S., Sarmah, B., Gupta, S., & Dwivedi, Y. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.12.001 · Cited by 591

e-Government Adoption Model (GAM): Differing service maturity levels

Shareef, M. A., Kumar, V., Kumar, U., & Dwivedi, Y. K. (2011) · Government Information Quarterly · doi:10.1016/j.giq.2010.05.006 · Cited by 581

Issues and recommendations for exploratory factor analysis and principal component analysis

Schreiber, J. B. (2021) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2020.07.027 · Cited by 565

Toward a model of social influence that explains minority student integration into the scientific community.

Estrada, M., Woodcock, A., Hernandez, P. R., & Schultz, P. W. (2011) · Journal of Educational Psychology · doi:10.1037/a0020743 · Cited by 546

Developmental cognitive neuroscience using latent change score models: A tutorial and applications

Kievit, R. A., Brandmaier, A. M., Ziegler, G., van Harmelen, A.-L., de Mooij, S. M. M., Moutoussis, M., Goodyer, I. M., Bullmore, E., Jones, P. B., Fonagy, P., et al. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.11.007 · Cited by 516

How Social Media Influencers Foster Relationships with Followers: The Roles of Source Credibility and Fairness in Parasocial Relationship and Product Interest

Yuan, S., & Lou, C. (2020) · Journal of Interactive Advertising · doi:10.1080/15252019.2020.1769514 · Cited by 543

Delineating components of emotion and its dysregulation in anxiety and mood psychopathology

Mennin, D. S., Holaway, R. M., Fresco, D. M., Moore, M. T., & Heimberg, R. G. (2007) · Behavior Therapy · doi:10.1016/j.beth.2006.09.001 · Cited by 527

The development of compassionate engagement and action scales for self and others

Gilbert, P., Catarino, F., Duarte, C., Matos, M., Kolts, R., Stubbs, J., Ceresatto, L., Duarte, J., Pinto-Gouveia, J., & Basran, J. (2017) · Journal of Compassionate Health Care · doi:10.1186/s40639-017-0033-3 · Cited by 527

Online learning performance and satisfaction: do perceptions and readiness matter?

Wei, H.-C., & Chou, C. (2020) · Distance Education · doi:10.1080/01587919.2020.1724768 · Cited by 529

Self-efficacy, job satisfaction, motivation and commitment: exploring the relationships between indicators of teachers’ professional identity

Canrinus, E. T., Helms-Lorenz, M., Beijaard, D., Buitink, J., & Hofman, A. (2012) · European Journal of Psychology of Education · doi:10.1007/s10212-011-0069-2 · Cited by 524

Exploring relationship development with social chatbots: A mixed-method study of replika

Pentina, I., Hancock, T., & Xie, T. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107600 · Cited by 522

The Future is Now: Reducing Psychological Distance to Increase Public Engagement with Climate Change

Jones, C., Hine, D. W., & Marks, A. D. G. (2017) · Risk Analysis · doi:10.1111/risa.12601 · Cited by 507

Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom

Yilmaz, R. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2016.12.085 · Cited by 514

Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model

Liu, G., & Ma, C. (2024) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2023.2240316 · Cited by 511

Self-regulation, self-efficacy, outcome expectations, and social support: Social cognitive theory and nutrition behavior

Anderson, E. S., Winett, R. A., & Wojcik, J. R. (2007) · Annals of Behavioral Medicine · doi:10.1007/bf02874555 · Cited by 500

The Fallacy of Formative Measurement

Edwards, J. R. (2011) · Organizational Research Methods · doi:10.1177/1094428110378369 · Cited by 495

Facebook addiction among Turkish college students: The role of psychological health, demographic, and usage characteristics

Koc, M., & Gulyagci, S. (2013) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2012.0249 · Cited by 487

Validation of the PHQ-9 in a psychiatric sample

Beard, C., Hsu, K. J., Rifkin, L. S., Busch, A. B., & Björgvinsson, T. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.12.075 · Cited by 467

The balanced measure of psychological needs (BMPN) scale: An alternative domain general measure of need satisfaction

Sheldon, K. M., & Hilpert, J. C. (2012) · Motivation and Emotion · doi:10.1007/s11031-012-9279-4 · Cited by 487

Impact of online information on self-isolation intention during the covid-19 pandemic: Cross-sectional study

Farooq, A., Laato, S., & Islam, A. K. M. N. (2020) · Journal of Medical Internet Research · doi:10.2196/19128 · Cited by 467

The moderating influence of environmental consciousness and recycling intentions on green purchase behavior

Kautish, P., Paul, J., & Sharma, R. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.04.389 · Cited by 476

The use of social media in travel information search

Chung, N., & Koo, C. (2015) · Telematics and Informatics · doi:10.1016/j.tele.2014.08.005 · Cited by 474

Using Principal Components and Factor Analysis in Animal Behaviour Research: Caveats and Guidelines

Budaev, S. V. (2010) · Ethology · doi:10.1111/j.1439-0310.2010.01758.x · Cited by 460

Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology

Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.04.017 · Cited by 468

Relationships between self-determination and postschool outcomes for youth with disabilities

Shogren, K. A., Wehmeyer, M. L., Palmer, S. B., Rifenbark, G. G., & Little, T. D. (2015) · The Journal of Special Education · doi:10.1177/0022466913489733 · Cited by 468

The Mediation Myth

Kline, R. B. (2015) · Basic and Applied Social Psychology · doi:10.1080/01973533.2015.1049349 · Cited by 460

The Hogg Eco-Anxiety Scale: Development and validation of a multidimensional scale

Hogg, T. L., Stanley, S. K., O'Brien, L. V., Wilson, M. S., & Watsford, C. R. (2021) · Global Environmental Change · doi:10.1016/j.gloenvcha.2021.102391 · Cited by 465

The impact of website quality on customer satisfaction, and purchase intention: perceived playfulness, and perceived flow as mediators.

Hsu, C.-L., Chang, K.-C., & Chen, M.-C. (2012) · Information Systems and e-Business Management · doi:10.1007/s10257-011-0181-5 · Cited by 451

The roles of associative and executive processes in creative cognition

Beaty, R. E., Silvia, P. J., Nusbaum, E. C., Jauk, E., & Benedek, M. (2014) · Memory & Cognition · doi:10.3758/s13421-014-0428-8 · Cited by 448

Examining the factor structure of the 39-item and 15-item versions of the Five Facet Mindfulness Questionnaire before and after mindfulness-based cognitive therapy for people with recurrent depression.

Gu, J., Strauss, C., Crane, C., Barnhofer, T., Karl, A., Cavanagh, K., & Kuyken, W. (2016) · Psychological Assessment · doi:10.1037/pas0000263 · Cited by 431

Progressing in the change journey towards sustainability in healthcare: The role of “Green” HRM

Pinzone, M., Guerci, M., Lettieri, E., & Redman, T. (2016) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.02.031 · Cited by 441

Instrumental leadership: Measurement and extension of transformational–transactional leadership theory

Antonakis, J., & House, R. J. (2014) · The Leadership Quarterly · doi:10.1016/j.leaqua.2014.04.005 · Cited by 440

Testing an integrated destination image model across residents and tourists

Stylidis, D., Shani, A., & Belhassen, Y. (2017) · Tourism Management · doi:10.1016/j.tourman.2016.10.014 · Cited by 440

On the Role of Passion for Work in Burnout: A Process Model

Vallerand, R. J., Paquet, Y., Philippe, F. L., & Charest, J. (2010) · Journal of Personality · doi:10.1111/j.1467-6494.2009.00616.x · Cited by 432

The Advertising Effects of Corporate Social Responsibility on Corporate Reputation and Brand Equity: Evidence from the Life Insurance Industry in Taiwan

Hsu, K.-T. (2012) · Journal of Business Ethics · doi:10.1007/s10551-011-1118-0 · Cited by 430

Modelling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students

Gökçearslan, Ş., Mumcu, F. K., Haşlaman, T., & Çevik, Y. D. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.091 · Cited by 424

MAILS - Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change- and meta-competencies

Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2023.100014 · Cited by 488

Refinement of the tripartite influence model for men: Dual body image pathways to body change behaviors

Tylka, T. L. (2011) · Body Image · doi:10.1016/j.bodyim.2011.04.008 · Cited by 411

Predicting the intentions to use chatbots for travel and tourism

Melián-González, S., Gutiérrez-Taño, D., & Bulchand-Gidumal, J. (2021) · Current Issues in Tourism · doi:10.1080/13683500.2019.1706457 · Cited by 406

The cognitive underpinnings of creative thought: a latent variable analysis exploring the roles of intelligence and working memory in three creative thinking processes

Lee, C. S., & Therriault, D. J. (2013) · Intelligence · doi:10.1016/j.intell.2013.04.008 · Cited by 402

Purchase intention toward organic food among young consumers using theory of planned behavior: role of environmental concerns and environmental awareness

Ahmed, N., Li, C., Khan, A., Qalati, S. A., Naz, S., & Rana, F. (2021) · Journal of Environmental Planning and Management · doi:10.1080/09640568.2020.1785404 · Cited by 393

Use of ChatGPT in academia: Academic integrity hangs in the balance

Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102370 · Cited by 394

Age Patterns in Risk Taking Across the World

Duell, N., Steinberg, L., Icenogle, G., Chein, J., Chaudhary, N., Di Giunta, L., Dodge, K. A., Fanti, K. A., Lansford, J. E., Oburu, P., et al. (2018) · Journal of Youth and Adolescence · doi:10.1007/s10964-017-0752-y · Cited by 374

What are the best outcome measurements for atopic eczema? A systematic review

Schmitt, J., Langan, S., & Williams, H. C. (2007) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2007.08.011 · Cited by 388

Organizational Change Recipients' Beliefs Scale: Development of an Assessment Instrument

Armenakis, A. A., Bernerth, J. B., Pitts, J. P., & Walker, H. J. (2007) · The Journal of Applied Behavioral Science · doi:10.1177/0021886307303654 · Cited by 386