DOI QR코드

DOI QR Code

Factor-analysis based questionnaire categorization method for reliability improvement of evaluation of working conditions in construction enterprises

  • Lin, Jeng-Wen (Department of Civil Engineering, Feng Chia University) ;
  • Shen, Pu Fun (Program in Civil and Hydraulic Engineering, Feng Chia University)
  • 투고 : 2014.01.13
  • 심사 : 2014.05.18
  • 발행 : 2014.09.25

초록

This paper presents a factor-analysis based questionnaire categorization method to improve the reliability of the evaluation of working conditions without influencing the completeness of the questionnaire both in Taiwanese and Chinese construction enterprises for structural engineering applications. The proposed approach springs from the AI application and expert systems in structural engineering. Questions with a similar response pattern are grouped into or categorized as one factor. Questions that form a single factor usually have higher reliability than the entire questionnaire, especially in the case when the questionnaire is complex and inconsistent. By classifying questions based on the meanings of the words used in them and the responded scores, reliability could be increased. The principle for classification was that 90% of the questions in the same classified group must satisfy the proposed classification rule and consequently the lowest one was 92%. The results show that the question classification method could improve the reliability of the questionnaires for at least 0.7. Compared to the question deletion method using SPSS, 75% of the questions left were verified the same as the results obtained by applying the classification method.

키워드

과제정보

연구 과제 주관 기관 : National Science Council

참고문헌

  1. Alexander, B., Monika, H., Benjamin, U., Alexander, H. and Reto, B. (2010), "Classification systems for tibial plateau fractures; Does computed tomography scanning improve their reliability", Injury, 41(2), 173-178. https://doi.org/10.1016/j.injury.2009.08.016
  2. Balling, R.J., Briggs, R.R. and Gillman, K. (2006), "Multiple optimum size/shape/topology designs for skeletal structures using a genetic algorithm", J. Struct. Eng., 132(7), 1158-1165. https://doi.org/10.1061/(ASCE)0733-9445(2006)132:7(1158)
  3. Chen, C.Y., Chen, Y.H., Yu, S.E., Chen, Y.W. and Li, C.C. (2012), "An integrate information technology model during earthquake dynamics", Struct. Eng. Mech., 44(5), 633-647. https://doi.org/10.12989/sem.2012.44.5.633
  4. Cheng, H., Fan, W., Yan, X.Y. and Philip, S.L. (2009), "Method and apparatus for structural data classification", United States Application US20090319457.
  5. Chiou, D.J., Hsu, W.K., Chen, C.W., Hsieh, C.M., Tang, J.P. and Chiang, W.L. (2011), "Applications of Hilbert- Huang transform to structural damage detection", Struct. Eng. Mech., 39(1), 1-20.
  6. Chokshi, D.S., Makwana, A.H. and Pitroda, J. (2013), "A preliminary study on importances of fly-ash bricks and clay bricks in construction industry through SPSS software", Int. J. Civil, Struct., Envir. Infrastr. Eng. Res. Develop., 3(5), 127-134.
  7. Chung, J.H., Consolazio, G.R., Dinan, R.J. and Rinehart, S.A. (2009), "Finite-element analysis of fluid-structure interaction in a blast-resistant window system", J. Struct. Eng., 136(3), 297-306.
  8. DeVellis, R.F. (1991), Scale Development Theory and Applications, Sage, London.
  9. DeVellis, R.F. (1998), Scale Development: Theory and Applications, Sage, CA.
  10. Drissi, Y. and Vilalta, R. (2011), "Methods and apparatus for generating a data classification model using an adaptive learning algorithm", United States Patent US7987144.
  11. Folino, G., Pizzuti, C. and Spezzano, G. (2006), "GP ensembles for large-scale data classification", IEEE Tran. Evol. Comput., 10(5), 604-616. https://doi.org/10.1109/TEVC.2005.863627
  12. Grierson, D.E. (1992), "A knowledge-based expert system for optimal structural design", Optimization and Artificial Intelligence in Civil and Structural Engineering, Springer Netherlands.
  13. Hackman, J.R. and Oldham, G.R. (1975), "Development of the job diagnostic survey", J. Appl. Psychol., 60, 159-170. https://doi.org/10.1037/h0076546
  14. Hurtado, J.E. and Alvarez, D.A. (2003), "Classification approach for reliability analysis with stochastic finite-element modeling", J. Struct. Eng., 129(8), 1141-1149. https://doi.org/10.1061/(ASCE)0733-9445(2003)129:8(1141)
  15. Jia, L. and Kuwamura, H. (2014), "Ductile fracture simulation of structural steels under monotonic tension", J. Struct. Eng., 140(5), 04013115. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000944
  16. Jia, L., Koyama, T. and Kuwamura, H. (2014), "Experimental and numerical study of postbuckling ductile fracture of heat-treated SHS stub columns", J. Struct. Eng., 140(7), 04014044 https://doi.org/10.1061/(ASCE)ST.1943-541X.0001056
  17. Juaim, M.N. and Hassanain, M.A. (2011), "Assessment of factors influencing the development and implementation of the architectural program", Struct. Sur., 29(4), 320-336. https://doi.org/10.1108/02630801111162387
  18. Kim, C.W., Kawatani, M., Ozaki, R. and Makihata, N. (2011), "Recovering missing data transmitted from a wireless sensor node for vibration-based bridge health monitoring", Struct. Eng. Mech., 38(4), 417-428. https://doi.org/10.12989/sem.2011.38.4.417
  19. Koike, T., Maruyama, O. and Garciano, L.E. (2007), "Ground strain estimation for lifeline earthquake engineering", Struct. Eng. Mech., 25(3), 291-310. https://doi.org/10.12989/sem.2007.25.3.291
  20. Liang, Q.Q. (2007), "Performance-based optimization: a review", Adv. Struct. Eng., 10(6), 739-753. https://doi.org/10.1260/136943307783571418
  21. Lin, J.W. (2001), "Adaptive algorithms for the identification of nonlinear structural systems", Ph.D. Dissertation, Columbia University, New York.
  22. Lin, J.W., Chen, C.W. and Hsu, T.C. (2012), "Fuzzy statistical refinement for the forecasting of tenders for roadway construction", J. Marine Sci. Tech., 20(4), 410-417.
  23. Lin, J.W., Chen, H.J. (2009), "Repetitive identification of structural systems using a nonlinear model parameter refinement approach", Shock Vib., 16(3), 229-240. https://doi.org/10.1155/2009/174917
  24. Lin, J.W. (2010), "Mode-by-mode evaluation of structural systems using a bandpass-HHT filtering approach", Struct. Eng. Mech., 36(6), 697-714. https://doi.org/10.12989/sem.2010.36.6.697
  25. Lin, J.W. (2011), "A hybrid algorithm based on EEMD and EMD for multi-mode signal processing", Struct. Eng. Mech., 39(6), 813-831. https://doi.org/10.12989/sem.2011.39.6.813
  26. Lin, J.W. (2012), "Fuzzy regression decision systems for assessment of the potential vulnerability of bridge to earthquakes", Nat. Hazard., 64(1), 211-221. https://doi.org/10.1007/s11069-012-0230-5
  27. Lin, J.W., Chen, C.W. and Hsu, T.C. (2013), "A novel regression prediction model for structural engineering applications", Struct. Eng. Mech., 45(5), 693-702. https://doi.org/10.12989/sem.2013.45.5.693
  28. Morone, D.J., and Sezen, H. (2014), "Simplified collapse analysis using data from building experiment", ACI Struct. J., 111(1-6), 925-934.
  29. Morshed, R. and Kazemi, M.T. (2005), "Seismic shear strengthening of R/C beams and columns with expanded steel meshed", Struct. Eng. Mech., 21(3), 333-350. https://doi.org/10.12989/sem.2005.21.3.333
  30. Nunnally, J.C. (1978), Psychometric Theory, 2nd Edition, McGraw-Hill, New York.
  31. O'Connor, A., Pedersen, C., Gustavsson, L. and Enevoldsen, I. (2009), "Probability-based assessment and optimised maintenance management of a large riveted truss railway bridge", Struct. Eng. Mech., 19(4), 375-382.
  32. Park, S., Kim, Y.B. and Stubbs, N. (2002), "Nondestructive damage detection in large structures via vibration monitoring", Electr. J. Struct. Eng., 2, 59-75.
  33. Porro-Munoz, D., Duin, R.P.W., Talavera, I. and Orozco-Alzate, M. (2011), "Classification of three-way data by the dissimilarity representation", Sig. Proc., 91(11), 2520-2529. https://doi.org/10.1016/j.sigpro.2011.05.004
  34. Rezakhani, P. (2011), "Fuzzy risk analysis model for construction projects", Int. J. Civil Struct. Eng., 2(2), 516-531.
  35. Schleif, F.M., Thomas, V. and Matthias, O. (2009), "Supervised data analysis and reliability estimation with exemplary application for spectral data", Neurocomput., 72(16-18), 3590-3601. https://doi.org/10.1016/j.neucom.2008.12.040
  36. Shih, B.Y., Chen, C.Y. and Su, W.L. (2012), "Construct OCR on mobile mechanic system for android wireless dynamics and structure stabilization", Struct. Eng. Mech., 42(5), 747-760. https://doi.org/10.12989/sem.2012.42.5.747
  37. Sun, Z. and Chang, C.C. (2004), "Statistical wavelet-based method for structural health monitoring", J. Struct. Eng., 130(7), 1055-1062. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:7(1055)
  38. Tseng, V.S. and Lee, C.H. (2009), "Effective temporal data classification by integrating sequential pattern mining and probabilistic induction", Expert Syst. Appl., 36(5), 9524-9532. https://doi.org/10.1016/j.eswa.2008.10.077
  39. Widaman, K.F., Grimm, K.J., Early, D.R., Robins, R.W. and Conger, R.D. (2013), "Investigating factorial invariance of latent variables across populations when manifest variables are missing completely", Struct. Eq. Model.: A Multidisc. J., 20(3), 384-408. https://doi.org/10.1080/10705511.2013.797819
  40. Will, T.M. and Powell, R. (1991), "A robust approach to the calculation of paleostress fields from fault plane data", J. Struct. Geol., 13(7), 813-821. https://doi.org/10.1016/0191-8141(91)90006-5
  41. Xu, Y. and Chen, J. (2012), "Fuzzy control for geometrically nonlinear vibration of piezoelectric flexible plates", Struct. Eng. Mech., 43(2), 163-177. https://doi.org/10.12989/sem.2012.43.2.163
  42. Yang, J. and Soh, C.K. (1998), "Discussion of genetic algorithms-based methodologies for design optimization of trusses", J. Struct. Eng., 124(8), 980-981. https://doi.org/10.1061/(ASCE)0733-9445(1998)124:8(980)

피인용 문헌

  1. Repetitive Model Refinement for Questionnaire Design Improvement in the Evaluation of Working Characteristics in Construction Enterprises vol.7, pp.12, 2015, https://doi.org/10.3390/su71115179
  2. Effects of Employees’ Work Values and Organizational Management on Corporate Performance for Chinese and Taiwanese Construction Enterprises vol.7, pp.12, 2015, https://doi.org/10.3390/su71215852