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Abstract

The paper aims to determine the criteria and sub-criteria for evaluating the contractor’s performance and finalize a master list of the criteria and sub-criteria to be used for evaluating contractor’s performance with their respective weights. The method is incorporated in the framework proposed for the evaluation of the contractor’s performance during the execution phase. An exploratory study has been opted, using a structured, close-ended multiple-choice questionnaire survey approach. The questionnaire survey was conducted in two phases, i.e. validation survey, and reliability survey. Fifteen experts responded to the validation survey, and thirty experts to the reliability survey. The experts were from Government and public sectors in India, working at various senior levels. The weights of criteria and sub-criteria were calculated from data collected in the survey, relative importance was calculated through the relative importance index and criteria were ranked. The paper provides criteria and subcriteria which were finalized through a questionnaire survey by classification of criteria identified in literature and tender review. The respective weights were finalized, which can be measured while evaluating contractors’ performance. The weights assigned to criteria through the survey are; health and safety is 13.19%, followed by finance 11.93%, time 11.93%, quality 13.38%, client satisfaction 12.42%, environmental safety 12.32%, productivity 12.51% and regulation 12.32%. The paper provides the criteria and sub-criteria with their weights needed for evaluating the performance of contractors during the project execution phase. This research can lead to a culture of continuous measurement of performance for the satisfactory completion of projects.
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Authors and Affiliations

Sunil Mahadik
1
ORCID: ORCID
Vinay Topkar
2
ORCID: ORCID

  1. Civil and Environmental Engineering Department, Veermata Jijabai Technological Institute, Mumbai, MH, India
  2. University of Michigan, Former Dy Director and Professor (Civil), Civil and Environmental Engineering Department, Veermata Jijabai Technological Institute, Mumbai, MH, India
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Abstract

A study was carried to assess the effect of traffic noise pollution on the work efficiency of shopkeepers in Indian urban areas. For this, an extensive literature survey was done on previous research done on similar topics. It was found that personal characteristics, noise levels in an area, working conditions of shopkeepers, type of task they are performing are the most significant factors to study effects on work efficiency. Noise monitoring, as well as a questionnaire survey, was done in Surat city to collect desired data. A total of 17 parameters were considered for assessing work efficiency under the influence of traffic noise. It is recommended that not more than 6 parameters should be considered for ANFIS modeling hence, before opting for the ANFIS modeling, most affecting parameters to work efficiency under the influence of traffic noise, was chosen by Structural Equation Model (SEM). As a result of the SEM model, two ANFIS prediction models were developed to predict the effect on work efficiency under the influence of traffic noise. R squared for model 1, for training data was 0.829 and for testing data, it was 0.727 and R squared for model 2 for training data was 0.828 and for testing data, it was 0.728. These two models can be used satisfactorily for predicting work efficiency under traffic noise environment for open shutter shopkeepers in tier II Indian cities.
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Bibliography

1. Aliabadi M., Golmohammadi R., Khotanlou H., Mansoorizadeh M., Salarpour A. (2015), Artificial neural networks and advanced fuzzy techniques for predicting noise level in the industrial embroidery workrooms, Applied Artificial Intelligence, 29(8): 766–785, doi: 10.1080/08839514.2015.1071090.
2. Azadeh A., Saberi M., Rouzbahman M., Valianpour F. (2015), A neuro-fuzzy algorithm for assessment of health, safety, environment and ergonomics in a large petrochemical plant, Journal of Loss Prevention in the Process Industries, 34: 100–114, doi: 10.1016/j.jlp.2015.01.008.
3. Banerjee D. (2012), Research on road traffic noise and human health in India: review of literature from 1991 to current, Noise & Health, 14(58): 113–118, doi: 10.4103/1463-1741.97255.
4. Bell P. (1980), Effects of heat, noise, and provocation on retaliatory evaluative behavior, Journal of Social Psychology, 110(1): 97–100, doi: 10.1080/00224545.1980.9924227.
5. Central Pollution Control Board, New Delhi, India (2002), Ambient Air Quality Standards in Respect of Noise.
6. Eriksson C., Nilsson M.E., Pershagen G. (2013), Environmental noise and health – Current knowledge and research needs, Swedish Environmetal Protection Agency Report 6553, Stockholm.
7. Ghosh S., Biswas S., Sarkar D., Sarkar P.P. (2014), A novel neuro-fuzzy classification technique for data mining, Egyptian Informatics Journal, 15(3): 129–147, doi: 10.1016/j.eij.2014.08.001.
8. Hancock P.A., Vasmatzidis I. (1998), Human occupational and performance limits under stress: The thermal environment as a prototypical example, Ergonomics, 41(8): 1169–1191, doi: 10.1080/001401398186469.
9. Ivoševic J., Bucak T., Andraši P. (2018), Effects of interior aircraft noise on pilot performance, Applied Acoustics, 139: 8–13, doi: 10.1016/j.apacoust.2018.04.006.
10. Khambete A.K., Christian R.A. (2014), Predicting efficiency of treatment plant by multi parameter aggregated index, Journal of Environmental Research and Development, 8(3): 530–539.
11. Liu W., Zhao T., Zhou W., Tang J. (2018), Safety risk factors of metro tunnel construction in China: An integrated study with EFA and SEM, Safety Science, 105: 98–113, doi: 10.1016/j.ssci.2018.01.009.
12. Mallick Z., Kaleel A.H., Siddiqui A.N. (2009), An expert system for predicting the effects of noise pollution on grass trimming task using fuzzy modeling, International Journal of Applied Environmental Sciences, 4(4): 389–403.
13. Norris M., Lecavalier L. (2010), Evaluating the use of exploratory factor analysis in developmental disability psychological research, Journal of Autism and Developmental Disorders, 40(1): 8–20, doi: 10.1007/ s10803-009-0816-2.
14. Pal D., Bhattacharya D. (2012), Effect of road traffic noise pollution on human work efficiency in government offices, private organizations, and commercial business centres in Agartala City using fuzzy expert system: A case study, Advances in Fuzzy Systems, 2012: Article ID 828593, doi: 10.1155/2012/828593.
15. Quartieri J., Mastorakis N.E., Guarnaccia C., Troisi A., D’Ambrosio S., Iannone G. (2009), Road intersections noise impact on urban environment quality, [in:] Recent Advances in Applied and Theoretical Mechanics. Proceedings of the 5th WSEAS International Conference on Applied and Theoretical Mechanics(MECHANICS’09), Puerto de la Cruz, Tenerife, Spain, pp. 162–171), WSEAS Press.
16. Rashid T. (2012), Fuzzy logic and neuro fuzzy models for direct current motors, International Journal of Engineering Inventions, 1(7): 68–75.
17. Recio A., Linares C., Banegas J.R., Díaz J. (2016), Road traffic noise effects on cardiovascular, respiratory, and metabolic health: An integrative model of biological mechanisms, Environmental Research, 146: 359– 370, doi: 10.1016/j.envres.2015.12.036.
18. Singh R., Ho L.J., Tan H.L., Bell P.A. (2007), Attitudes, personal evaluations, cognitive evaluation and interpersonal attraction: On the direct, indirect and reverse-causal effects, British Journal of Social Psychology, 46: 19–42, doi: 10.1348/014466606X104417.
19. Tandel B., Macwan J.E.M. (2017), Road traffic noise exposure and hearing impairment among traffic policemen in Surat, Western India, Journal of The Institution of Engineers (India), Series A, 98: 101–105, doi: 10.1007/s40030-017-0210-6.
20. Thompson B. (2004), Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications, American Psychological Association,Washington DC.
21. Tiwari S., Babbar R., Kaur G. (2018), Performance evaluation of two ANFIS models for predicting water quality index of River Satluj (India), Advances in Civil Engineering, 2018: Article ID 8971079, doi: 10.1155/2018/8971079.
22. Yadav M., Tandel B. (2019), Exposure effect study of traffic noise on roadside shopkeepers in Surat City, Indian Journal of Environmental Protection, 39: 1038– 1045.
23. Yadav M., Tandel B. (2021), Structural equation model-based selection and strength Co-relation of variables for work performance efficiency under traffic noise exposure, Archives of Acoustics, 46(1): 155–166, doi: 10.24425/aoa.2021.136569.
24. Zaheeruddin (2006), Modelling of noise-induced annoyance: a neuro-fuzzy approach, 2006 IEEE International Conference on Industrial Technology, 2006, pp. 2686–2691, doi: 10.1109/ICIT.2006.372676.
25. Zaheeruddin, Garima (2006), A neuro-fuzzy approach for prediction of human work efficiency in noisy environment, Applied Soft Computing, 6(3): 283–294, doi: 10.1016/j.asoc.2005.02.001.
26. Zaheeruddin, Jain V.K. (2008), An expert system for predicting the effects of speech interference due to noise pollution on humans using fuzzy approach, Expert Systems with Applications, 35, 1978–1988, doi: 10.1016/j.eswa.2007.08.104.
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Authors and Affiliations

Manoj Yadav
1
ORCID: ORCID
Bhaven Tandel
1

  1. Civil Engineering Department, S. V. National Institute of Technology, Surat, India
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Abstract

The aim of the study was to evaluate the tourism and recreational space of Lubaczowski County in Poland. The evaluation was carried out by using a multidimensional comparative analysis while taking into account tourism assets, transportation accessibility, natural environmental protection, the level of tourism infrastructure development as well as the factors contributing to an opportunity for the development of tourism via investment attractiveness (the level of infrastructure development, population relations, or the financial situation of the communes). Moreover, a questionnaire survey was carried out among the inhabitants with the aim of learning of their opinions on tourism assets and tourism infrastructure development in the commune. The study is supplemented by a comparison of the analysis results with the results of a questionnaire survey conducted among the Lubaczowski County inhabitants, which concerned the county’s attractiveness to tourists. Based on the evaluation and the questionnaire survey results, it was found that urban communes of Lubaczów and Horyniec-Zdrój had the best conditions for tourism development. These communes took the first (0.701) and the second (0.492) position in the ranking, respectively. Both communes are characterised by well-developed accommodation and catering facilities, a wealth of natural assets, and good transportation accessibility. For the better development of tourism in the county, it is necessary to take appropriate measures aimed at eliminating limitations and highlighting the strengths. To this end, it will be necessary to incorporate measures aimed at enhancing the quality of tourism infrastructure development and establishing a marketing plan that will allow tourists to learn about the tourism assets of the commune into the strategy for commune development.

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Authors and Affiliations

Agnieszka Ziernicka-Wojtaszek
ORCID: ORCID
Marta Lisiak

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