Predicting sustainability assessment at early facilities design phase

Facilities ◽  
2017 ◽  
Vol 35 (7/8) ◽  
pp. 388-404 ◽  
Author(s):  
Valentina Zileska Pancovska ◽  
Silvana Petrusheva ◽  
Aleksandar Petrovski
Keyword(s):  
Predictive Model ◽  
Work Experience ◽  
Sustainability Assessment ◽  
Project Managers ◽  
General Regression Neural Network ◽  
Percentage Error ◽  
Preliminary Design ◽  
Design Phase ◽  
Content Type ◽  
Facilities Design

PurposeIntegrating the aspects of sustainability into facilities design has become a designers’ challenge, and the early design phase is seen as the most important in implementing sustainability into facilities design. Therefore, this paper aims to analyze the factors that influence sustainability assessment of preliminary design of facilities and predicts sustainability assessment depending on those factors. Design/methodology/approachData were collected by survey questionnaire distributed to project managers using a six-point Likert scale. Obtained data were modeled with general regression neural network (GRNN) using DTREG software. In total, 27 factors were chosen for determining the most accurate predictive model, and their importance was computed. FindingsThe six most important factors for sustainability assessment of facilities design are: work experience, work on several outline design proposals, resolving issues between stakeholders, prioritization of participants in the design phase, procurement management and defining projects’ program and goals. The predictive model that was used for prediction of the sustainability assessment was shown to be highly accurate, with MAPE (mean absolute percentage error) amounting to 2.58 per cent. Practical implicationsUsing the same approach, assessment of every other factor for the preliminary design can be predicted and the factors that are most influential to its sustainability can be obtained. Originality/valueThe paper supports the sustainability improvement of the preliminary design of future facilities’ projects, as well as support during the decision-making process.

Design, analysis and optimization of thin walled semi-monocoque wing structures using different structural idealization in the preliminary design phase

2014 ◽  
Vol 5 (3) ◽  
pp. 214-226 ◽  
Author(s):  
Odeh Dababneh ◽  
Altan Kayran
Keyword(s):  
Finite Element ◽  
Structural Analysis ◽  
Design Analysis ◽  
Preliminary Design ◽  
Two Dimensional ◽  
Design Phase ◽  
Content Type ◽  
Wing Structures ◽  
Wing Structure ◽  
Thin Walled

Purpose – In modeling an aircraft wing, structural idealizations are often employed in hand calculations to simplify the structural analysis. In real applications of structural design, analysis and optimization, finite element methods are used because of the complexity of the geometry, combined and complex loading conditions. The purpose of this paper is to give a comprehensive study on the effect of using different structural idealizations on the design, analysis and optimization of thin walled semi-monocoque wing structures in the preliminary design phase. Design/methodology/approach – In the design part of the paper, wing structures are designed by employing two different structural idealizations that are typically used in the preliminary design phase. In the structural analysis part, finite element analysis of one of the designed wing configurations is performed using six different one and two dimensional finite element pairs which are typically used to model the sub-elements of semi-monocoque wing structures. Finally in the optimization part, wing structure is optimized for minimum weight by using finite element models which have the same six different finite element pairs used in the analysis phase. Findings – Based on the results presented in the paper, it is concluded that with the simplified methods, preliminary sizing of the wing configurations can be performed with enough confidence as long as the simplified method based designs are also optimized iteratively, which is what is practiced in the design phase of this study. Originality/value – This research aims at investigating the effect of using different one and two dimensional element pairs on the final analyzed and optimized configurations of the wing structure, and conclusions are inferred with regard to the sensitivity of the optimized wing configurations with respect to the choice of different element types in the finite element model.

Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market

2020 ◽  
Vol 13 (1) ◽  
pp. 16-26
Author(s):  
Sumit Saroha ◽  
Sanjeev K. Aggarwal
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Wavelet Transform ◽  
Wind Power ◽  
Electricity Market ◽  
General Regression Neural Network ◽  
Percentage Error ◽  
Wind Power Forecasting ◽  
General Regression ◽  
Power Forecasting

Objective: The estimation accuracy of wind power is an important subject of concern for reliable grid operations and taking part in open access. So, with an objective to improve the wind power forecasting accuracy. Methods: This article presents Wavelet Transform (WT) based General Regression Neural Network (GRNN) with statistical time series input selection technique. Results: The results of the proposed model are compared with four different models namely naïve benchmark model, feed forward neural networks, recurrent neural networks and GRNN on the basis of Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) performance metric. Conclusion: The historical data used by the presented models has been collected from the Ontario Electricity Market for the year 2011 to 2015 and tested for a long time period of more than two years (28 months) from November 2012 to February 2015 with one month estimation moving window.

PROMETHEE-based ranking of project managers based on the five personality traits

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1083-1102
Author(s):  
Georgios N. Aretoulis ◽  
Jason Papathanasiou ◽  
Fani Antoniou
Keyword(s):  
Personality Traits ◽  
Questionnaire Survey ◽  
Multicriteria Decision Making ◽  
Project Managers ◽  
Preference Ranking ◽  
Infrastructure Projects ◽  
Public Infrastructure ◽  
Content Type ◽  
The One ◽  
Selection Of

Purpose This paper aims to rank and identify the most efficient project managers (PMs) based on personality traits, using Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) methodology. Design/methodology/approach The proposed methodology relies on the five personality traits. These were used as the selection criteria. A questionnaire survey among 82 experienced engineers was used to estimate the required weights per personality trait. A second two-part questionnaire survey aimed at recording the PMs profile and assess the performance of personality traits per PM. PMs with the most years of experience are selected to be ranked through Visual PROMETHEE. Findings The findings suggest that a competent PM is the one that scores low on the “Neuroticism” trait and high especially on the “Conscientiousness” trait. Research limitations/implications The research applied a psychometric test specifically designed for Greek people. Furthermore, the proposed methodology is based on the personality characteristics to rank the PMs and does not consider the technical skills. Furthermore, the type of project is not considered in the process of ranking PMs. Practical implications The findings could contribute in the selection of the best PM that maximizes the project team’s performance. Social implications Improved project team communication and collaboration leading to improved project performance through better communication and collaboration. This is an additional benefit for the society, especially in the delivery of public infrastructure projects. A lot of public infrastructure projects deviate largely as far as cost and schedule is concerned and this is an additional burden for public and society. Proper project management through efficient PMs would save people’s money and time. Originality/value Identification of the best PMbased on a combination of multicriteria decision-making and psychometric tests, which focus on personality traits.

scholarly journals Musculoskeletal disorders among rice farmers in Phimai District, Nakhon Ratchasima Province, Thailand

2019 ◽  
Vol 33 (6) ◽  
pp. 494-503
Author(s):  
Ekarat Sombatsawat ◽  
Titaporn Luangwilai ◽  
Parichat Ong-artborirak ◽  
Wattasit Siriwong
Keyword(s):  
Musculoskeletal Disorders ◽  
Work Experience ◽  
Rank Correlation ◽  
Agricultural Practices ◽  
Farm Size ◽  
Body Region ◽  
Cross Sectional ◽  
Content Type ◽  
Rice Farmers ◽  
Body Regions

Purpose The purpose of this paper is to explore the prevalence of musculoskeletal disorders (MSDs) and determine factors influencing MSDs among rice farmers. Design/methodology/approach A cross-sectional study was carried out among 156 rice farmers from 14 villages in Tarnlalord sub-district, Phimai district, Nakhon Ratchasima province, Thailand, from February 2017 to March 2017. Face-to-face interviews, including demographics, work characteristics and musculoskeletal pain, were conducted using a modified standardized Nordic questionnaire. Findings The results revealed that both 78 males and 78 females participated in the study to which the average of age and body mass index (BMI) was 45.5±11.4 years and 24.9±4.0 kg/m2, respectively. All rice farmers reported MSDs in at least one body region during the six months preceding the interview. The highest prevalence of MSDs showed 86.5 percent in the lower back area, followed by 85.9 percent in the neck, and 80.7 percent in the shoulders. The analysis of binary logistic regression and Spearman’s rank correlation showed that factors such as gender, age, BMI, work experience and farm size influence MSDs’ occurrence, and pain severity in one or more body regions (p < 0.05). Originality/value Musculoskeletal injuries are a significant health problem in rice farmers. The study indicated that appropriate agricultural practices such as working posture, equipment size selection and carrying loads should be recommended to prevent MSDs. Thus, the occupational health and safety services in agricultural workers are needed.

Perceived value of internship experience: a try before you leap

2018 ◽  
Vol 8 (4) ◽  
pp. 376-394 ◽  
Author(s):  
Sonali Bhattacharya ◽  
Netra Neelam
Keyword(s):  
Experiential Learning ◽  
Performance Feedback ◽  
Work Experience ◽  
Selection Process ◽  
Learning Orientation ◽  
Research Approach ◽  
Content Type ◽  
Internship Experience ◽  
And Performance ◽  
Task Variety

Purpose The purpose of this paper is to examine how internship value is manifested in the context of a business school. The authors have examined the internship experience in terms of experiential learning and employability. Specifically, the authors investigate the factors that determine internship at four phases: design, conduct, evaluation and feedback. Design/methodology/approach The authors have applied a mixed method approach. In all, 110 students of a busines school were first surveyed on their expectation, motivation and level of preparation through a self-administered questionnaire before internship. Based on the survey result, eight of these students were interviewed in details about internship expectations from industry, the selection process for internship, communications or exchanges between intern and companies prior to internship and perceived industry expectation from interns. At the next phase, authors used a qualitative research approach by conducting semi-structured, in-depth interviews with 14 interns and their mentors after internship period. They were interviewed on design, conduct, evaluation and feedback process of the internship. Interviews tried capture what kind of leader-member exchange led to satisfactory internship experience and outcome from view of both inter and mentor. Findings The authors find that at various stages of internship program quality of mentor – intern exchanges (as defined by leadership exchange theory), and task characteristics as indicated by autonomy, task variety, task significance and performance feedback determine intern’s performance. An intern’s performance is antecedent to an intern’s and a mentor’s satisfaction and overall internship value. The authors also found that intrinsic capability of intern such as critical thinking ability and learning orientation result in enhanced value of internship experience. The proposed models, postulate that at designing stage, lower the level of communication from employers, higher the feeling of ambiguity and lower the perceived internship value in terms of experiential learning and perceived employability. Feeling of ambiguity is moderated by existence of prior work experience of interns. At conduction stage, mentor-intern exchange is directly related to flexibility in structure of the program and inversely related to dependency on peer learning. Mentor-intern exchange also related to mentor and intern’s learning value. However, the learning value is moderated by learning orientation of the intern. Originality/value The authors have tried the summer internship experience from the perspective of interns and mentors. This is the uniqueness of the research.

How project managers can encourage and develop positive emotions in project teams

2014 ◽  
Vol 7 (3) ◽  
pp. 449-472 ◽  
Author(s):  
Morten Emil Berg ◽  
Jan Terje Karlsen
Keyword(s):  
Empirical Data ◽  
Positive Emotions ◽  
Project Managers ◽  
Engineering Industry ◽  
Project Teams ◽  
Future Research ◽  
Content Type ◽  
Team Members ◽  
Signature Strengths ◽  
Positive Meaning

Purpose – This study provides insight into how project managers can use leadership tools to encourage and develop positive emotions among the project team members toward greater overall project success. The purpose of this paper is to provide the engineering industry with a closer look at how positive emotions can create good team member relations, reduce stress, develop clearer roles, creativity and joy at the workplace. Design/methodology/approach – The empirical data were obtained using in-depth interviews of three experienced project managers. Findings – The empirical data give insight as to how project managers can use their signature strengths. Additionally, the data also show how they can evolve and draw on positive meaning, positive emotions and positive relations. Various examples of positive meaning, positive emotions, positive relations and signature strengths have been identified and discussed. Research limitations/implications – Future research should apply a more comprehensive research design, for example a survey using a larger sample, so that these findings may be generalized. Practical implications – The paper contributes to portray and analyze positive psychology in a project management setting. Additionally, the paper assists understanding the connections among positive meaning, positive emotions, positive relations and signature strengths by presenting and discussing a model. Originality/value – This research extends current understanding of how project managers use their signature strengths to encourage and develop positive emotions in project teams.

Civil engineers’ personal values/demographics linkage in project team building

2017 ◽  
Vol 24 (6) ◽  
pp. 1337-1349 ◽  
Author(s):  
Atilla Damci ◽  
David Arditi ◽  
Gul Polat
Keyword(s):  
Statistical Analysis ◽  
Work Experience ◽  
Personal Values ◽  
Team Building ◽  
Project Teams ◽  
Team Leaders ◽  
Content Type ◽  
First Time ◽  
The Relationship ◽  
Civil Engineers

Purpose The purpose of this paper is to explore the relationship between civil engineers’ demographics (e.g. age, marital status, education, work experience) and their personal values. The objective was to predict civil engineers’ personal values based on their demographics. Design/methodology/approach A questionnaire survey was administered to civil engineers to collect data on their demographics and their personal values. Statistical analysis was performed to verify whether a significant statistical relationship exists between civil engineers’ demographics and their personal values. Findings The most important and the least important personal values were identified for civil engineers. Statistical analysis indicated that civil engineers’ values do vary based on their demographics. Research limitations/implications The results of this study cannot be generalized, because individuals’ personal values and demographics are, by definition, local. Location and culture may affect the personal values of civil engineers. Practical implications Team leaders normally have access to information about the demographics of the engineers they employ; based on the results of this study, they should be able to predict their personal values, and to make more informed decisions when appointing them to particular positions on project teams. Originality/value The research presented in this paper, establishes for the first time, that a linkage exists between civil engineers’ personal values and their demographics, and makes it easier for team leaders to make assignment decisions.

Antecedents of growth-oriented entrepreneurship before and during the Greek economic crisis

2017 ◽  
Vol 24 (3) ◽  
pp. 528-544 ◽  
Author(s):  
Ioannis Giotopoulos ◽  
Alexandra Kontolaimou ◽  
Aggelos Tsakanikas
Keyword(s):  
Work Experience ◽  
Early Stage ◽  
New Ventures ◽  
High Growth ◽  
Content Type ◽  
Crisis Period ◽  
Individual Level ◽  
Level Data ◽  
The Social ◽  
Before And After

Purpose The purpose of this paper is to explore potential drivers of high-growth intentions of early-stage entrepreneurs in Greece before and after the onset of the financial crisis of 2008. Design/methodology/approach To this end, the authors use individual-level data retrieved from Global Entrepreneurship Monitor annual surveys (2003-2015). Findings The results show that high-growth intentions of Greek entrepreneurs are driven by different factors in the crisis compared to the non-crisis period. Male entrepreneurs and entrepreneurs with significant work experience seem to be more likely to be engaged in growth-oriented new ventures during the crisis period. The same appears to hold for entrepreneurs who are motivated by an opportunity and also perceive future business opportunities in adverse economic conditions. On the other hand, the educational level and the social contacts of founders with other entrepreneurs are found to drive ambitious Greek entrepreneurship in the years before the crisis, while they were insignificant after the crisis outbreak. Originality/value Based on the concept of ambitious entrepreneurship, this study contributes to the literature by investigating the determinants of entrepreneurial high-growth expectations in the Greek context emphasizing the crisis period in comparison to the pre-crisis years.

Online versus offline: preferred retail choice for premium brand purchase

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rituparna Basu ◽  
Neena Sondhi
Keyword(s):  
Predictive Model ◽  
Logit Analysis ◽  
Chi Square ◽  
Content Type ◽  
Sales Personnel ◽  
Study Results ◽  
Shopping Experience ◽  
Brick And Mortar ◽  
Chi Square Analysis ◽  
Retail Format

PurposeThis exploratory study aims to examine the prevalent triggers that motivate a premium brand purchase in an online vs offline retail format.Design/methodology/approachA binary logit analysis is used to build a predictive model to assess the likelihood of the premium brand consumer seeking an online or an offline platform. Demographic and usage-based profile of the two set of consumers is established through a chi-square analysis.FindingsThree hundred and forty six urban consumers of premium branded apparels residing in two Indian Metros were studied. A predictive model with 89.6% accuracy was validated for distinguishing premium brand buyers who shop at brick-and-mortar store or online platforms. Quality and finish were factors sought by the online buyer, whereas autotelic need, pleasurable shopping experience and social approval were important triggers for an in-store purchase.Research limitations/implicationsThe study posits divergent demographics and motivational drivers that led to an online vs offline purchase. Though interesting and directional, the study results need to be examined across geographies and categories for establishing the generalizability of the findings.Practical implicationsThe study findings indicate that premium brand manufacturers can devise an omni-channel strategy that is largely tilted toward the online platform, as the quality conscious and brand aware consumer is confident and thus open to an online purchase. The implication for the physical outlet on the other hand is to ensure exclusive store atmospherics and knowledgeable but non-intrusive sales personnel.Originality/valueThe study is unique as it successfully builds a predictive model to forecast online vs offline purchase decisions among urban millennials.

Comparing predictive performance of general regression neural network (GRNN) and hedonic regression model for factors affecting housing prices in “Pune-India”

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhijat Arun Abhyankar ◽  
Harish Kumar Singla
Keyword(s):  
Neural Network ◽  
Regression Model ◽  
Multivariate Regression ◽  
Housing Prices ◽  
Predictive Performance ◽  
General Regression Neural Network ◽  
Multivariate Regression Model ◽  
Data Set ◽  
Content Type ◽  
General Regression

Purpose The purpose of this study is to compare the predictive performance of the hedonic multivariate regression model with the probabilistic neural network (PNN)-based general regression neural network (GRNN) model of housing prices in “Pune-India.” Design/methodology/approach Data on 211 properties across “Pune city-India” is collected. The price per square feet is considered as a dependent variable whereas distances from important landmarks such as railway station, fort, university, airport, hospital, temple, parks, solid waste site and stadium are considered as independent variables along with a dummy for amenities. The data is analyzed using a hedonic type multivariate regression model and GRNN. The GRNN divides the entire data set into two sets, namely, training set and testing set and establishes a functional relationship between the dependent and target variables based on the probability density function of the training data (Alomair and Garrouch, 2016). Findings While comparing the performance of the hedonic multivariate regression model and PNN-based GRNN, the study finds that the output variable (i.e. price) has been accurately predicted by the GRNN model. All the 42 observations of the testing set are correctly classified giving an accuracy rate of 100%. According to Cortez (2015), a value close to 100% indicates that the model can correctly classify the test data set. Further, the root mean square error (RMSE) value for the final testing for the GRNN model is 0.089 compared to 0.146 for the hedonic multivariate regression model. A lesser value of RMSE indicates that the model contains smaller errors and is a better fit. Therefore, it is concluded that GRNN is a better model to predict the housing price functions. The distance from the solid waste site has the highest degree of variable senstivity impact on the housing prices (22.59%) followed by distance from university (17.78%) and fort (17.73%). Research limitations/implications The study being a “case” is restricted to a particular geographic location hence, the findings of the study cannot be generalized. Further, as the objective of the study is restricted to just to compare the predictive performance of two models, it is felt appropriate to restrict the scope of work by focusing only on “location specific hedonic factors,” as determinants of housing prices. Practical implications The study opens up a new dimension for scholars working in the field of housing prices/valuation. Authors do not rule out the use of traditional statistical techniques such as ordinary least square regression but strongly recommend that it is high time scholars use advanced statistical methods to develop the domain. The application of GRNN, artificial intelligence or other techniques such as auto regressive integrated moving average and vector auto regression modeling helps analyze the data in a much more sophisticated manner and help come up with more robust and conclusive evidence. Originality/value To the best of the author’s knowledge, it is the first case study that compares the predictive performance of the hedonic multivariate regression model with the PNN-based GRNN model for housing prices in India.

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