Research Article
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Year 2021, Volume: 8 Issue: 3, 318 - 326, 29.09.2021

Abstract

References

  • Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics, 2(4), 433-459. doi:10.1002/wics.101
  • Ambreen, N., Khan, S., & Fatima, U. (2019). A Survey on Contemporary Inventory Techniques and Problems Faced By Manufacturing Organizations in Pakistan. In: Proceedings of 2019 IEEE 10th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT) (pp. 157-160). IEEE. doi:10.1109/ICMIMT.2019.8712008
  • Bagozzi, R. P. (2011). Measurement and meaning in information systems and organizational research: Methodological and philosophical foundations. MIS Quarterly, 35(2), 261-292. doi:10.2307/23044044
  • Boyes, A., Girgis, A., & Lecathelinais, C. (2009). Brief assessment of adult cancer patients' perceived needs: development and validation of the 34‐item Supportive Care Needs Survey (SCNS‐SF34). Journal of Evaluation in Clinical Practice, 15(4), 602-606. doi:10.1111/j.1365-2753.2008.01057.x
  • Brosnan, K., Grün, B., & Dolnicar, S. (2018). Identifying superfluous survey items. Journal of Retailing and Consumer Services, 43, 39-45. doi:10.1016/j.jretconser.2018.02.007
  • Cervellera, C., Wen, A., & Chen, V. C. P. (2007). Neural network and regression spline value function approximations for stochastic dynamic programming. Computers & Operations Research, 34(1), 70-90. doi:10.1016/j.cor.2005.02.043
  • Dolnicar, S. (2013). Asking good survey questions. Journal of Travel Research, 52(5), 551-574. doi:10.1177/0047287513479842
  • Fan, W., & Yan, Z. (2010). Factors affecting response rates of the web survey: A systematic review. Computers in Human Behavior, 26(2), 132-139. doi:10.1016/j.chb.2009.10.015
  • Garcia-Diaz, A., & Phillips, D. T. (1995). Principles of experimental design and analysis. Springer.
  • Gopalakrishnan, K., & Stinson, D. R. (2006). Applications of orthogonal arrays to computer science. In: Proc. of ICDM (pp. 149-164).
  • Ho, W., & Ma, X. (2018). The state-of-the-art integrations and applications of the analytic hierarchy process. European Journal of Operational Research, 267(2), 399-414. doi:10.1016/j.ejor.2017.09.007
  • Hoerger, M. (2010). Participant dropout as a function of survey length in Internet-mediated university studies: Implications for study design and voluntary participation in psychological research. Cyberpsychology, Behavior, and Social Networking, 13(6), 697-700. doi:10.1089/cyber.2009.0445
  • Kolenikov, S. (2010). Resampling variance estimation for complex survey data. The Stata Journal, 10(2), 165-199. doi:10.1177/1536867X1001000201
  • Liao, H., Xu, Z., & Zeng, X. J. (2015). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 1343-1355. doi:10.1109/TFUZZ.2014.2360556
  • Meimand, S. E., Khalifah, Z., Zavadskas, E. K., Mardani, A., Najafipour, A. A., & Ahmad, U. N. U. (2017). Residents’ attitude toward tourism development: A sociocultural perspective. Sustainability, 9(7), 1170. doi:10.3390/su9071170
  • Mi, X., Li, J., Liao, H., Kazimieras Zavadskas, E., Al-Barakati, A., Barnawi, A., & Herrera-Viedma, E. (2019). Hospitality brand management by a score-based q-rung ortho pair fuzzy VIKOR method integrated with the best worst method. Economic Research, 32(1), 3266-3295. doi:10.1080/1331677X.2019.1658533
  • Otchere, A. F., Adzimah, E. D., & Aikens, I. (2016). Assessing the inventory management practices in a selected company in Ghana. International Journal of Development and Sustainability, 5(3), 105-19, ISDS Article ID: IJDS14122701
  • Sloane, N. J. A. (2007) "A Library of Orthogonal Arrays" http://neilsloane.com/oadir/
  • Verma, R., & Thompson, G. M. (1996). Basing service management on customer determinants: the importance of hot pizza. The Cornell Hotel and Restaurant Administration Quarterly, 37(3), 18-23. doi:10.1016/0010-8804(96)86809-1
  • Vetschera, R. (2017). Deriving rankings from incomplete preference information: A comparison of different approaches. European Journal of Operational Research, 258(1), 244-253. doi:10.1016/j.ejor.2016.08.031
  • Yager, R. R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25(5), 1222-1230. doi:10.1109/TFUZZ.2016.2604005

Designing an Effective Questionnaire using Orthogonal Array for Improving Inventory Accuracy at Electricity Warehouse

Year 2021, Volume: 8 Issue: 3, 318 - 326, 29.09.2021

Abstract

The process of classical data collection through a survey is time-consuming, expensive, and may not be feasible. In practice, it is always good to make sure that the survey design works with the diversity of factors and levels that affect the products or services. Since the data quality gathered depends solely on the quality of the survey constructed and the written questions, this paper presents one of the most effective tools in designing a stated-choice survey using orthogonal array design to gather the information that improves the inventory accuracy in electricity company’s warehouses. The stated-choice survey provides an effective way to explore survey respondents’ preferences and evaluate the interchanges that survey respondents make in considering several product and service combinations. This method will help inventory engineers and workers for data collection with more information and a minimum number of questions and efforts.

References

  • Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics, 2(4), 433-459. doi:10.1002/wics.101
  • Ambreen, N., Khan, S., & Fatima, U. (2019). A Survey on Contemporary Inventory Techniques and Problems Faced By Manufacturing Organizations in Pakistan. In: Proceedings of 2019 IEEE 10th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT) (pp. 157-160). IEEE. doi:10.1109/ICMIMT.2019.8712008
  • Bagozzi, R. P. (2011). Measurement and meaning in information systems and organizational research: Methodological and philosophical foundations. MIS Quarterly, 35(2), 261-292. doi:10.2307/23044044
  • Boyes, A., Girgis, A., & Lecathelinais, C. (2009). Brief assessment of adult cancer patients' perceived needs: development and validation of the 34‐item Supportive Care Needs Survey (SCNS‐SF34). Journal of Evaluation in Clinical Practice, 15(4), 602-606. doi:10.1111/j.1365-2753.2008.01057.x
  • Brosnan, K., Grün, B., & Dolnicar, S. (2018). Identifying superfluous survey items. Journal of Retailing and Consumer Services, 43, 39-45. doi:10.1016/j.jretconser.2018.02.007
  • Cervellera, C., Wen, A., & Chen, V. C. P. (2007). Neural network and regression spline value function approximations for stochastic dynamic programming. Computers & Operations Research, 34(1), 70-90. doi:10.1016/j.cor.2005.02.043
  • Dolnicar, S. (2013). Asking good survey questions. Journal of Travel Research, 52(5), 551-574. doi:10.1177/0047287513479842
  • Fan, W., & Yan, Z. (2010). Factors affecting response rates of the web survey: A systematic review. Computers in Human Behavior, 26(2), 132-139. doi:10.1016/j.chb.2009.10.015
  • Garcia-Diaz, A., & Phillips, D. T. (1995). Principles of experimental design and analysis. Springer.
  • Gopalakrishnan, K., & Stinson, D. R. (2006). Applications of orthogonal arrays to computer science. In: Proc. of ICDM (pp. 149-164).
  • Ho, W., & Ma, X. (2018). The state-of-the-art integrations and applications of the analytic hierarchy process. European Journal of Operational Research, 267(2), 399-414. doi:10.1016/j.ejor.2017.09.007
  • Hoerger, M. (2010). Participant dropout as a function of survey length in Internet-mediated university studies: Implications for study design and voluntary participation in psychological research. Cyberpsychology, Behavior, and Social Networking, 13(6), 697-700. doi:10.1089/cyber.2009.0445
  • Kolenikov, S. (2010). Resampling variance estimation for complex survey data. The Stata Journal, 10(2), 165-199. doi:10.1177/1536867X1001000201
  • Liao, H., Xu, Z., & Zeng, X. J. (2015). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 1343-1355. doi:10.1109/TFUZZ.2014.2360556
  • Meimand, S. E., Khalifah, Z., Zavadskas, E. K., Mardani, A., Najafipour, A. A., & Ahmad, U. N. U. (2017). Residents’ attitude toward tourism development: A sociocultural perspective. Sustainability, 9(7), 1170. doi:10.3390/su9071170
  • Mi, X., Li, J., Liao, H., Kazimieras Zavadskas, E., Al-Barakati, A., Barnawi, A., & Herrera-Viedma, E. (2019). Hospitality brand management by a score-based q-rung ortho pair fuzzy VIKOR method integrated with the best worst method. Economic Research, 32(1), 3266-3295. doi:10.1080/1331677X.2019.1658533
  • Otchere, A. F., Adzimah, E. D., & Aikens, I. (2016). Assessing the inventory management practices in a selected company in Ghana. International Journal of Development and Sustainability, 5(3), 105-19, ISDS Article ID: IJDS14122701
  • Sloane, N. J. A. (2007) "A Library of Orthogonal Arrays" http://neilsloane.com/oadir/
  • Verma, R., & Thompson, G. M. (1996). Basing service management on customer determinants: the importance of hot pizza. The Cornell Hotel and Restaurant Administration Quarterly, 37(3), 18-23. doi:10.1016/0010-8804(96)86809-1
  • Vetschera, R. (2017). Deriving rankings from incomplete preference information: A comparison of different approaches. European Journal of Operational Research, 258(1), 244-253. doi:10.1016/j.ejor.2016.08.031
  • Yager, R. R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems, 25(5), 1222-1230. doi:10.1109/TFUZZ.2016.2604005
There are 21 citations in total.

Details

Primary Language English
Journal Section Industrial Engineering
Authors

Abdulaziz Alkabaa 0000-0001-9016-4241

Osman Taylan 0000-0002-5806-3237

Publication Date September 29, 2021
Submission Date April 28, 2021
Published in Issue Year 2021 Volume: 8 Issue: 3

Cite

APA Alkabaa, A., & Taylan, O. (2021). Designing an Effective Questionnaire using Orthogonal Array for Improving Inventory Accuracy at Electricity Warehouse. Gazi University Journal of Science Part A: Engineering and Innovation, 8(3), 318-326.