International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

line decor
  
line decor

 Volume 11, Issue 2 (February 2024), Pages: 16-24

----------------------------------------------

 Original Research Paper

Development and validation of a scale for measuring organizational behavior: A comprehensive approach

 Author(s): 

 Laongsri Niangchaem 1, Khahan Na-Nan 2, *, Kanakarn Phanniphong 1

 Affiliation(s):

 1Faculty of Business Administration and Information Technology, Rajamangala University of Technology Tawan-Ok, Bangkok, Thailand
 2Faculty of Business Administration, Rajamangala University of Technology Thanyaburi, Pathum Thani, Thailand

 Full text

  Full Text - PDF

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-5679-1070

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.02.003

 Abstract

Organizational behavior has long been a focus for researchers and academicians, and it is crucial for individual, team, and organizational achievements. There are debates about how to accurately measure organizational behavior, and existing scales have limitations. This paper offers a detailed view of developing scales in organizational behavior studies. This includes creating items, assessing content validity, pilot testing, refining items, validating the scale, and collecting data. The scale's validity and reliability are confirmed using statistical methods like exploratory and confirmatory factor analysis. The analysis results show the scale's legitimacy through factor loadings and reliability. The final scale is described, detailing the number of items and their specific dimensions. The discussion highlights the scale's benefits and limitations, its practical uses in organizational behavior research, and future research suggestions. This article is a thorough guide for researchers on creating effective and dependable measurement tools in organizational behavior.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Scale development, Organizational behavior, Content validity, Item refinement, Scale validation

 Article history

 Received 28 September 2023, Received in revised form 16 January 2024, Accepted 17 January 2024

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Niangchaem L, Na-Nan K, and Phanniphong K (2024). Development and validation of a scale for measuring organizational behavior: A comprehensive approach. International Journal of Advanced and Applied Sciences, 11(2): 16-24

 Permanent Link to this page

 Figures

 Fig. 1  

 Tables

 No Table

----------------------------------------------   

 References (49)

  1. Abualrub RF and Alghamdi MG (2012). The impact of leadership styles on nurses’ satisfaction and intention to stay among Saudi nurses. Journal of Nursing Management, 20(5): 668-678. https://doi.org/10.1111/j.1365-2834.2011.01320.x   [Google Scholar] PMid:22823223
  2. Ansari S and Rashidian A (2012). Guidelines for guidelines: Are they up to the task? A comparative assessment of clinical practice guideline development handbooks. PLOS ONE, 7(11): e49864. https://doi.org/10.1371/journal.pone.0049864   [Google Scholar] PMid:23189167 PMCid:PMC3506587
  3. Borman WC and Motowidlo SJ (1997). Task performance and contextual performance: The meaning for personnel selection research. Human Performance, 10(2): 99-109. https://doi.org/10.1207/s15327043hup1002_3   [Google Scholar]
  4. Brown TA (2015). Confirmatory factor analysis for applied research. Guilford Publications, New York, USA.   [Google Scholar]
  5. Burnes B and Hughes M (2023). Organizational change, leadership and ethics. Taylor and Francis, Oxfordshire, UK. https://doi.org/10.4324/9781003036395-19   [Google Scholar]
  6. Busque-Carrier M, Le Corff Y, and Ratelle CF (2022). Development and validation of the integrative work values scale. European Review of Applied Psychology, 72(5): 100766. https://doi.org/10.1016/j.erap.2022.100766   [Google Scholar]
  7. Byrne BM (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge, New York, USA. https://doi.org/10.4324/9781315757421   [Google Scholar]
  8. Cacciotti G, Hayton JC, Mitchell JR, and Allen DG (2020). Entrepreneurial fear of failure: Scale development and validation. Journal of Business Venturing, 35(5): 106041. https://doi.org/10.1016/j.jbusvent.2020.106041   [Google Scholar]
  9. DeVellis RF and Thorpe CT (2021). Scale development: Theory and applications. SAGE Publications, Thousand Oaks, USA.   [Google Scholar]
  10. Ferguson E and Cox T (1993). Exploratory factor analysis: A users’ guide. International Journal of Selection and Assessment, 1(2): 84-94. https://doi.org/10.1111/j.1468-2389.1993.tb00092.x   [Google Scholar]
  11. Finch WH (2020). Using fit statistic differences to determine the optimal number of factors to retain in an exploratory factor analysis. Educational and Psychological Measurement, 80(2): 217-241. https://doi.org/10.1177/0013164419865769   [Google Scholar] PMid:32158020 PMCid:PMC7047263
  12. Finney SJ (2007). Book review: Exploratory and confirmatory factor analysis: Understanding concepts and applications. Applied Psychological Measurement, 31(3): 245-248. https://doi.org/10.1177/0146621606290168   [Google Scholar]
  13. Ford LR and Scandura TA (2018). A typology of threats to construct validity in item generation. American Journal of Management, 18(2): 132-142. https://doi.org/10.33423/ajm.v18i2.298   [Google Scholar]
  14. Gaasedelen OJ, Whiteside DM, Altmaier E, Welch C, and Basso MR (2019). The construction and the initial validation of the cognitive bias scale for the personality assessment inventory. The Clinical Neuropsychologist, 33(8): 1467-1484. https://doi.org/10.1080/13854046.2019.1612947   [Google Scholar] PMid:31092108
  15. Goretzko D and Bühner M (2022). Robustness of factor solutions in exploratory factor analysis. Behaviormetrika, 49(1): 131-148. https://doi.org/10.1007/s41237-021-00152-w   [Google Scholar]
  16. Grenier RS (2021). Identifying and measuring expertise in organizations. In: Germain ML and Grenier RS (Eds.), Expertise at work: Current and emerging trends: 57-69. Palgrave Macmillan, Cham, Switzerland. https://doi.org/10.1007/978-3-030-64371-3_4   [Google Scholar]
  17. Hair JF, Black WC, Babin BJ, and Anderson RE (2019). Multivariate data analysis. 8th Edition, Cengage Learning, Boston, USA.   [Google Scholar]
  18. Hellmann JH, Schlechter P, Knausenberger J, Bollwerk M, Geukes K, and Back MD (2022). Measuring perceived realistic physical threat imposed by migrants: Scale development and validation. European Journal of Psychological Assessment, 38(4): 332-342. https://doi.org/10.1027/1015-5759/a000668   [Google Scholar]
  19. Hinkin TR (1995). A review of scale development practices in the study of organizations. Journal of Management, 21(5): 967-988. https://doi.org/10.1016/0149-2063(95)90050-0   [Google Scholar]
  20. House RJ and Rizzo JR (1972). Toward the measurement of organizational practices: Scale development and validation. Journal of Applied Psychology, 56(5): 388-396. https://doi.org/10.1037/h0033444   [Google Scholar]
  21. Hoyle RH (2012). Handbook of structural equation modeling. Guilford Press, New York, USA.   [Google Scholar]
  22. Irvine SH and Kyllonen PC (2013). Item generation for test development. Routledge, London, UK. https://doi.org/10.4324/9781410602145   [Google Scholar]
  23. Jung S (2013). Exploratory factor analysis with small sample sizes: A comparison of three approaches. Behavioural Processes, 97: 90-95. https://doi.org/10.1016/j.beproc.2012.11.016   [Google Scholar] PMid:23541772
  24. Khalid K and Eldakak SE (2018). Exploratory and confirmatory factor analysis for validating the moral competency questionnaire. Advanced Science Letters, 24(7): 5094-5097. https://doi.org/10.1166/asl.2018.11275   [Google Scholar]
  25. King C, Grace D, and Funk DC (2012). Employee brand equity: Scale development and validation. Journal of Brand Management, 19: 268-288. https://doi.org/10.1057/bm.2011.44   [Google Scholar]
  26. King D and Lawley S (2022). Organizational behaviour. Oxford University Press, Oxford, UK. https://doi.org/10.1093/hebz/9780192893475.001.0001   [Google Scholar]
  27. Kitreerawutiwong K, Sriruecha C, and Laohasiriwong W (2015). Development of the competency scale for primary care managers in Thailand: Scale development. BMC Family Practice, 16: 174. https://doi.org/10.1186/s12875-015-0388-5   [Google Scholar] PMid:26646942 PMCid:PMC4673780
  28. Kline RB (2023). Principles and practice of structural equation modeling. Guilford Publications, New York, USA.   [Google Scholar]
  29. Kump B, Engelmann A, Kessler A, and Schweiger C (2019). Toward a dynamic capabilities scale: Measuring organizational sensing, seizing, and transforming capacities. Industrial and Corporate Change, 28(5): 1149-1172. https://doi.org/10.1093/icc/dty054   [Google Scholar]
  30. Kyriazos TA and Stalikas A (2018). Applied psychometrics: The steps of scale development and standardization process. Psychology, 9(11): 2531-2560. https://doi.org/10.4236/psych.2018.911145   [Google Scholar]
  31. Levett-Jones T, McCoy M, Lapkin S, Noble D, Hoffman K, Dempsey J, and Roche J (2011). The development and psychometric testing of the satisfaction with simulation experience scale. Nurse Education Today, 31(7): 705-710. https://doi.org/10.1016/j.nedt.2011.01.004   [Google Scholar] PMid:21288606
  32. Moorman RH (1993). The influence of cognitive and affective based job satisfaction measures on the relationship between satisfaction and organizational citizenship behavior. Human Relations, 46(6): 759-776. https://doi.org/10.1177/001872679304600604   [Google Scholar]
  33. Morgeson FP and Hofmann DA (1999). The structure and function of collective constructs: Implications for multilevel research and theory development. Academy of Management Review, 24(2): 249-265. https://doi.org/10.5465/amr.1999.1893935   [Google Scholar]
  34. Newsom JT (2015). Longitudinal structural equation modeling: A comprehensive introduction. Routledge, London, UK. https://doi.org/10.4324/9781315871318   [Google Scholar]
  35. Olson K (2010). An examination of questionnaire evaluation by expert reviewers. Field Methods, 22(4): 295-318. https://doi.org/10.1177/1525822X10379795   [Google Scholar]
  36. Podsakoff PM, MacKenzie SB, Lee JY, and Podsakoff NP (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5): 879-903. https://doi.org/10.1037/0021-9010.88.5.879   [Google Scholar] PMid:14516251
  37. Rahman MM (2023). Sample size determination for survey research and non-probability sampling techniques: A review and set of recommendations. Journal of Entrepreneurship, Business and Economics, 11(1): 42-62.   [Google Scholar]
  38. Robbins S, Judge TA, Millett B, and Boyle M (2013). Organisational behaviour. Pearson Higher Education, Sydney, Australia.   [Google Scholar]
  39. Robbins SP, Judge TA, and Vohra N (2019). Organisational behaviour. Pearson Education India, Bengaluru, India.   [Google Scholar]
  40. Rowan N and Wulff D (2007). Using qualitative methods to inform scale development. Qualitative Report, 12(3): 450-466.   [Google Scholar]
  41. Rowley J (2012). Conducting research interviews. Management Research Review, 35(3/4): 260-271. https://doi.org/10.1108/01409171211210154   [Google Scholar]
  42. Sharma G (2017). Pros and cons of different sampling techniques. International Journal of Applied Research, 3(7): 749-752.   [Google Scholar]
  43. Smith GT and McCarthy DM (1995). Methodological considerations in the refinement of clinical assessment instruments. Psychological Assessment, 7(3): 300-308. https://doi.org/10.1037//1040-3590.7.3.300   [Google Scholar]
  44. Stratman JK and Roth AV (2002). Enterprise resource planning (ERP) competence constructs: Two‐stage multi‐item scale development and validation. Decision Sciences, 33(4): 601-628. https://doi.org/10.1111/j.1540-5915.2002.tb01658.x   [Google Scholar]
  45. Streiner DL, Norman GR, and Cairney J (2015). Health measurement scales: A practical guide to their development and use. Oxford University Press, Cary, USA. https://doi.org/10.1093/med/9780199685219.001.0001   [Google Scholar]
  46. Sürücü L and Maslakci A (2020). Validity and reliability in quantitative research. Business and Management Studies: An International Journal, 8(3): 2694-2726. https://doi.org/10.15295/bmij.v8i3.1540   [Google Scholar]
  47. Taber KS (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48: 1273-1296. https://doi.org/10.1007/s11165-016-9602-2   [Google Scholar]
  48. Wut TM, Lee D, Ip WM, and Lee SW (2021). Digital sustainability in the organization: Scale development and validation. Sustainability, 13(6): 3530. https://doi.org/10.3390/su13063530   [Google Scholar]
  49. Zhou Y (2019). A mixed methods model of scale development and validation analysis. Measurement: Interdisciplinary Research and Perspectives, 17(1): 38-47. https://doi.org/10.1080/15366367.2018.1479088   [Google Scholar]