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Abstract

For the construction company, tendering is the most popular way of acquiring contracts. The decision to participate in the tender needs to be made carefully, as it affects the condition of the company and is an important aspect in its quest for success. The bid/no bid decision making is a complex process involving a number of factors. The research carried out so far has mainly concerned the identification of the various kinds of influences on contractors’ bidding decisions. The researchers, on the basis of contractors’ opinions, created rank lists in an attempt to categorize the factors. In this paper the author employs factor analysis which belongs to basic methods of multi-dimensional data analysis. The paper’s aim is first to depict an output set of observed variables, that is bid/no bid factors, in terms of a smaller set of latent variables which cannot be directly observed and then to interpret the dependencies between them.

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Authors and Affiliations

A. Leśniak
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Abstract

A speaker recognition system based on joint factor analysis (JFA) is proposed to improve whispering speakers’ recognition rate under channel mismatch. The system estimated separately the eigenvoice and the eigenchannel before calculating the corresponding speaker and the channel factors. Finally, a channel-free speaker model was built to describe accurately a speaker using model compensation. The test results from the whispered speech databases obtained under eight different channels showed that the correct recognition rate of a recognition system based on JFA was higher than that of the Gaussian Mixture Model-Universal Background Model. In particular, the recognition rate in cellphone channel tests increased significantly.

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Authors and Affiliations

Gang Lv
Heming Zhao
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Abstract

The selection of the formwork system for high rise building affects the entire construction project duration and cost. The study reports the factors influencing the selection of different formwork system in the construction of high rise buildings through structural questionnaire survey from the client, contractor, consultant, and interviews with expert members. Total of 40 technical factors was identified from the literature and 220 filled questionnaires were received from the respondent. Relative Importance Index method is used to find the topmost factors affecting the selection of formwork system. Additionally, from factor analysis 22 factors were identified to have a correlation with one another. Regression analysis reveals that duration of the project, maintenance cost, adaptability, and safety have impact on formwork selection across time, cost and quality. These findings could potentially increase the construction company’s existing knowledge in relation to formwork selection.

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Authors and Affiliations

Viswanathan Rajeshkumar
V. Sreevidya
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Abstract

Enterprise innovation is currently becoming a recognized factor of the competitiveness, survival, and development of companies in the market economy. Managers still need recommendations on ways of stimulating the growth of innovation in their companies. The objective of this paper is to identify the strategic factors of enterprise innovativeness in the area of technology, defined as the most important internal factors positively impacting the innovativeness of enterprises in a strategic perspective. Empirical studies were conducted using the Computer-Assisted Web Interview (CAWI) method on a purposive sample of N = 180 small and medium-sized innovative industrial processing enterprises in Poland. Data analysis was performed using Exploratory Factor Analysis within the Confirmatory Factor Analysis framework (E-CFA) and Structural Equation Modeling (SEM). Empirical research shows that the strategic factor of enterprise innovativeness in the area of technology is technological activity. A technologically active company should (1) possess a modern machinery stock, (2) conduct systematic technological audits, and (3) maintain close technical cooperation with the suppliers of raw materials, consumables, and intermediates. The implementation of the indicated recommendations by managers should lead to increased innovativeness of small and medium-sized industrial companies. The author recommends the use of the presented research procedure and data analysis methods in further studies.
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Authors and Affiliations

Danuta Rojek
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Abstract

In the study, environmetric methods were successfully performed a) to explore natural and anthropogenic controls on reservoir water quality, b) to investigate spatial and temporal differences in quality, and c) to determine quality variables discriminating three reservoirs in Izmir, Turkey. Results showed that overall water quality was mainly governed by “natural factors” in the whole region. A parameter that was the most important in contributing to water quality variation for one reservoir was not important for another. Between summer and winter periods, difference in arsenic concentrations were statistically significant in the Tahtalı, Ürkmez and iron concentrations were in the Balçova reservoirs. Observation of high/low levels in two seasons was explained by different processes as for instance, dilution from runoff at times of high flow seeped through soil and entered the river along with the rainwater run-off and adsorption. Three variables “boron, arsenic and sulphate” discriminated quality among Balçova & Tahtalı, Balçova & Ürkmez and two variables “zinc and arsenic” among the Tahtalı & Ürkmez reservoirs. The results illustrated the usefulness of multivariate statistical techniques to fingerprint pollution sources and investigate temporal/spatial variations in water quality.

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Authors and Affiliations

Hülya Boyacioglu
Hayal Boyacioglu
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Abstract

The purpose of the work was to determine the relationship between the of the water quality parameters in an artificial reservoir used as cooling ponds. Multivariate methods, cluster analysis and factor analysis were applied to analyze eighteen physico-chemical parameters such as air and water temperature, dissolved oxygen concentration, visibility of the Secchi disk, concentrations of total nitrogen, ammonium, nitrate, nitrite, total phosphorus, phosphate, concentrations of calcium, magnesium, chlorides, sulfates and total dissolved salts, pH, chemical oxygen demand and electric conductivity from 2002-2017 to investigated cooling water discharge. Hierarchical cluster analysis (CA) allowed identified five different clusters that reflect the different water quality characteristics of the water system. Similar results were obtained in exploratory factor analysis, five factors were obtained with 65.96% total variance. However, confirmatory factor analysis showed that four latent variables: salinity, temperature, eutrophication, and ammonia provide better fit to the data than a five-factor structure. Correlations between latent variables temperature, eutrophication and ammonia show a significant effect of temperature on the transformation of nitrogen and phosphorus compounds.
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Authors and Affiliations

Jerzy Mazierski
1
Maciej Kostecki
1
ORCID: ORCID

  1. Institute of Environmental Engineering, Polish Academy of Sciences, Poland
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Abstract

The aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.

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Authors and Affiliations

Danijela Voza
Milovan Vukovic
Ljiljana Takic
Djordje Nikolic
Ivana Mladenovic-Ranisavljevic
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Abstract

In the study suitability of water quality index approach and environmetric methods in fi ngerprinting heavy metal pollution as well as comparison of spatial variability of multiple contaminants in surface water were assessed in the case of The Gediz River Basin, Turkey. Water quality variables were categorized into two classes using factor and cluster analysis. Furthermore, soil contamination index was adapted to water pollution index and used to fi nd out the relative relationship between the reference standards and the current situation of heavy metal contamination in water. Results revealed that surface water heavy metal content was mainly governed by metal processing, textile and tannery industries in the region. On the other hand, metal processing industry discharges mainly degraded quality of water in Kemalpasa and Menemen. Furthermore, Kemalpasa region has been heavily affected from tannery and textile industries effl uents. Moreover, pollution parameters have not been infl uenced by changes in physical factors (discharge and temperature). This study indicated the effectiveness of water quality index approach and statistical tools in fi ngerprinting of pollution and comparative assessment of water quality. Both methods can assist decision makers to determine priorities in management practices.
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Authors and Affiliations

Hülya Boyacioglu
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Abstract

Lean manufacturing has been the most deliberated concept ever since its introduction. Many organization across the world implemented lean concept and witnessed dramatic improvements in all contemporary performance parameters. Lean manufacturing has been a sort of mirage for the Indian automotive industry. The present research investigated the key lean barriers to lean implementation through literature survey, confirmatory factor analysis, multiple regression, and analytic network process. The general factors to lean implementation were inadequate lean planning, resource constraints, half-hearted commitment from management, and behavioral issues. The most important factor in the context of lean implementation in Indian automotive industry was inadequate lean planning found with the help of confirmatory factor analysis and multiple regression analysis. Further analysis of these extracted factors through analytic network process suggested the key lean barriers in Indian automotive industry, starting from the most important were absence of proper lean implementation methodology, lack of customer focus, absence of proper lean measurement system, inadequate capital, improper selection of lean tools & practices, leadership issues, resistance to change, and poorly defined roles & responsibilities. Though literature identifying various lean barriers are available. The novelty of current research emerges from the identification and subsequent prioritization of key lean barriers within Indian automotive SMEs environment. The research assists in smooth transition from traditional to lean system by identifying key barriers and developing customized framework of lean implementation for Indian automotive SMEs.
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Authors and Affiliations

Rupesh Kumar Tiwari
Jeetendra Kumar Tiwari
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Abstract

Indian SMEs are going to play pivotal role in transforming Indian economy and achieving

double digit growth rate in near future. Performance of Indian SMEs is vital in making

India as a most preferred manufacturing destination worldwide under India’s “Make in India

Policy”. Current research was based on Indian automotive SMEs. Indian automotive SMEs

must develop significant agile capability in order to remain competitive in highly uncertain

global environment. One of the objectives of the research was to find various enablers of

agility through literature survey. Thereafter questionnaire administered exploratory factor

analysis was performed to extract various factors of agility relevant in Indian automotive

SMEs environment. Multiple regression analysis was applied to assess the relative importance

of these extracted factors. “Responsiveness” was the most important factor followed by

“Ability to reconfigure”, “Ability to collaborate”, and “Competency”. Thereafter fuzzy logic

bases algorithm was applied to assess the current level of agility of Indian automotive SMEs.

It was found as “Slightly Agile”, which was the deviation from the targeted level of agility.

Fuzzy ranking methodology facilitated the identification & criticalities of various barriers

to agility, so that necessary measures can be taken to improve the current agility level of

Indian automotive SMEs. The current research may helpful in finding; key enablers of agility,

assessing the level of agility, and ranking of the various enablers of agility to point out the

weak zone of agility so that subsequent corrective action may be taken in any industrial

environment similar to India automotive SMEs.

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Authors and Affiliations

Rupesh Kumar Tiwari
Jeetendra Kumar Tiwari
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Abstract

In this work, we integrated exploratory factor analysis (EFA) followed by structural equation modelling (SEM) to assess the work performance efficiency under the traffic noise environment for open shutter shopkeepers in the Indian urban context. 706 valid questionnaire responses by personal interviews in local language were collected from open shutter shopkeepers exposed to noise level (Leq) of 77 dBA for 12 to 14 hours daily. The questionnaire was prepared based on demographics, environmental conditions, and primary effects of noise pollution. Among which four common latent factors which summaries 17 questionnaire response items were obtained by exploratory factor analysis, which are “Impacts of noise” (IM), “Environmental conditions” (EC), “Personal characteristics” (PC) and “Work efficiency” (WE). The associations between the individual latent factors were studied by the structural equation model method in AMOS software. Validation of the constructed model was carried out by testing the proposed hypothesis as well as goodness-of-fit indices like Absolute fit, Incremental fit, and Parsimonious fit indices. The effect of specific latent factors derived on the work efficiency of shopkeepers in the noisy area was characterized by the path coefficients estimated in the SEM model. It was found that work performance efficiency (WE) was greatly influenced by the primary impacts of noise pollution like annoyance, stress, interference in spoken communication, which was associated with the latent factor “Impacts of noise” (IM) with a path coefficient of 0.931. The second latent factor “Environmental conditions” (EC), which was associated with parameters like ambient temperature and humidity, showed less path coefficient of 0.153. And lastly, a latent factor called “Personal characteristics” (PC) associated with age, experience, education, showed the least path coefficient of 0.05. The work efficiency of open shutter shopkeepers working in a highly noisy commercial area is profoundly affected by the prominent effects of noise pollution and least affected by ambient environmental conditions as well as their personal characteristics. The developed model clarified some casual relationships among complex systems in the study of noise exposure on individuals n tier 2 cities in the Indian context and may help other researchers to study of tier I and tier III cities.
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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 Shatt Al Arab River (SAAR) is a major source of raw water for most water treatment plants (WTP’s) located along with it in Basrah province. This study aims to determine the effects of different variables on water quality of the SAAR, using multivariate statistical analysis. Seventeen variables were measured in nine WTP’s during 2017, these sites are Al Hussain (1), Awaissan (2), Al Abass (3), Al Garma (4), Mhaigran (5), Al Asmaee (6), Al Jubaila (7), Al Baradia (8), Al Lebani (9). The dataset is treated using principal component analysis (PCA) / factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of contamination and the suitability of water for drinking and irrigation. Three factors are responsible for the data structure representing 88.86% of the total variance in the dataset. CA shows three different groups of similarity between the sampling stations, in which station 5 (Mhaigran) is more contami-nated than others, while station 3 (Al Abass) and 6 (Al Asmaee) are less contaminated. Electrical conductivity (EC) and sodium adsorption ratio (SAR) are plotted on Richard diagram. It is shown that the samples of water of Mhaigran are locat-ed in the class of C4-S3 of very high salinity and sodium, water samples of Al Abass station, are located in the class of C3-S1 of high salinity and low sodium, and others are located in the class of C4-S2 of high salinity and medium sodium. Generally, the results of most water quality parameters reveal that SAAR is not within the permissible levels of drinking and irrigation.

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Authors and Affiliations

Zainb A.A. Al Saad
ORCID: ORCID
Ahmed N.A. Hamdan
ORCID: ORCID

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