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Repetitive Model Refinement for Questionnaire Design Improvement in the Evaluation of Working Characteristics in Construction Enterprises

Author

Listed:
  • Jeng-Wen Lin

    (Department of Civil Engineering, Feng Chia University, Taichung 407, Taiwan)

  • Pu Fun Shen

    (Ph.D. Program in Civil and Hydraulic Engineering, Feng Chia University, Taichung 407, Taiwan)

  • Bing-Jean Lee

    (Department of Civil Engineering, Feng Chia University, Taichung 407, Taiwan)

Abstract

This paper presents an iterative confidence interval based parametric refinement approach for questionnaire design improvement in the evaluation of working characteristics in construction enterprises. This refinement approach utilizes the 95% confidence interval of the estimated parameters of the model to determine their statistical significance in a least-squares regression setting. If this confidence interval of particular parameters covers the zero value, it is statistically valid to remove such parameters from the model and their corresponding questions from the designed questionnaire. The remaining parameters repetitively undergo this sifting process until their statistical significance cannot be improved. This repetitive model refinement approach is implemented in efficient questionnaire design by using both linear series and Taylor series models to remove non-contributing questions while keeping significant questions that are contributive to the issues studied, i.e. , employees’ work performance being explained by their work values and cadres’ organizational commitment being explained by their organizational management. Reducing the number of questions alleviates the respondent burden and reduces costs. The results show that the statistical significance of the sifted contributing questions is decreased with a total mean relative change of 49%, while the Taylor series model increases the R -squared value by 17% compared with the linear series model.

Suggested Citation

  • Jeng-Wen Lin & Pu Fun Shen & Bing-Jean Lee, 2015. "Repetitive Model Refinement for Questionnaire Design Improvement in the Evaluation of Working Characteristics in Construction Enterprises," Sustainability, MDPI, vol. 7(11), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:11:p:15179-15193:d:58971
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    References listed on IDEAS

    as
    1. Daji Ergu & Gang Kou, 2012. "Questionnaire design improvement and missing item scores estimation for rapid and efficient decision making," Annals of Operations Research, Springer, vol. 197(1), pages 5-23, August.
    2. Dominic D. Ahiaga-Dagbui & Simon D. Smith, 2014. "Dealing with construction cost overruns using data mining," Construction Management and Economics, Taylor & Francis Journals, vol. 32(7-8), pages 682-694, August.
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    Cited by:

    1. Na Zhang & Zijia Wang & Feng Chen & Jingni Song & Jianpo Wang & Yu Li, 2020. "Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji," Energies, MDPI, vol. 13(4), pages 1-18, February.
    2. Feng Chen & Xiaopeng Shen & Zijia Wang & Yang Yang, 2017. "An Evaluation of the Low-Carbon Effects of Urban Rail Based on Mode Shifts," Sustainability, MDPI, vol. 9(3), pages 1-12, March.
    3. Jeng-Wen Lin & Pu Fun Shen & Yin-Sung Hsu, 2015. "Effects of Employees’ Work Values and Organizational Management on Corporate Performance for Chinese and Taiwanese Construction Enterprises," Sustainability, MDPI, vol. 7(12), pages 1-13, December.

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