Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073534
K. Dhamodharan, P. Balasubramanian, Deepti Mohan
This paper analyses the influence of Yamaganda period in investor's decision to trade, based on the relationship between Yamaganda timing and Stock trading volume using minuteby minute data(combined fromtick data) of Nifty 200 companies traded at India's National Stock Exchange (NSE) for the period of one year from July 1, 2014 to June 30, 2015 (This period consists of 245 Trading days) and is done using Big data tool Spark. Yamaganda is an Indian cultural variable; it is a time period defined in the astrology which is considered inauspicious. The study is done on Yamaganda period, Non-Yamaganda period, Pre-Yamaganda period (half an hour before Yamaganda Period) & Post-Yamaganda Period (half an hour after Yamaganda period). The analysis shows that this cultural variable has very less impact on the Trading decisions of investors. A separate test done only on Tuesday (in order to eliminate day of the week effect and further the absence of Yamaganda period in the trading hours of Wednesday and Thursday) also shows that this cultural variable has very less impact on the Trading decisions of the investors.
{"title":"Influence of yamaganda on stock trading behaviour among Nifty200 stocks: Using minute-wise data","authors":"K. Dhamodharan, P. Balasubramanian, Deepti Mohan","doi":"10.1109/ICDMAI.2017.8073534","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073534","url":null,"abstract":"This paper analyses the influence of Yamaganda period in investor's decision to trade, based on the relationship between Yamaganda timing and Stock trading volume using minuteby minute data(combined fromtick data) of Nifty 200 companies traded at India's National Stock Exchange (NSE) for the period of one year from July 1, 2014 to June 30, 2015 (This period consists of 245 Trading days) and is done using Big data tool Spark. Yamaganda is an Indian cultural variable; it is a time period defined in the astrology which is considered inauspicious. The study is done on Yamaganda period, Non-Yamaganda period, Pre-Yamaganda period (half an hour before Yamaganda Period) & Post-Yamaganda Period (half an hour after Yamaganda period). The analysis shows that this cultural variable has very less impact on the Trading decisions of investors. A separate test done only on Tuesday (in order to eliminate day of the week effect and further the absence of Yamaganda period in the trading hours of Wednesday and Thursday) also shows that this cultural variable has very less impact on the Trading decisions of the investors.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123817896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073502
Vishnu Tharavath, Deepak Gupta, S. Gunasekar
Eating out has evolved from being a behavior associated with the mere benefit of functionality to a more hedonic one. It has become an act of socializing with preference of cuisines changing according to various parameters. The purpose of this study was to develop a model to understand the factors affecting the choice of cuisines while Indian consumers eat out. The study was conducted among 172 respondents from all over India using online surveys. The sample was identified through Quota sampling. Ordered logistic regressions were employed to find the influence of various factors like methods of seeking entertainment, reason(s) for eating out in a restaurant, expectations from a restaurant and personality, on the preference of cuisines such as Indian, Chinese, Italian, French and Arabic while eating out. The study reveals that these factors influence the preference of cuisines differently. For example, the personality of an individual has significant influence over the preference of Indian and Arabic cuisines while people who give more importance to the quality of food while eating out are more likely to prefer Indian cuisine. Furthermore, this study also reveals that as the age of people increases, their preference towards Indian cuisine increases whereas preference towards Italian cuisine decreases, while eating out. Young consumers who eat out for good food and variety of dishes are more likely to prefer Italian cuisine.
{"title":"Factors influencing choice of cuisines while Indian consumers eat out","authors":"Vishnu Tharavath, Deepak Gupta, S. Gunasekar","doi":"10.1109/ICDMAI.2017.8073502","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073502","url":null,"abstract":"Eating out has evolved from being a behavior associated with the mere benefit of functionality to a more hedonic one. It has become an act of socializing with preference of cuisines changing according to various parameters. The purpose of this study was to develop a model to understand the factors affecting the choice of cuisines while Indian consumers eat out. The study was conducted among 172 respondents from all over India using online surveys. The sample was identified through Quota sampling. Ordered logistic regressions were employed to find the influence of various factors like methods of seeking entertainment, reason(s) for eating out in a restaurant, expectations from a restaurant and personality, on the preference of cuisines such as Indian, Chinese, Italian, French and Arabic while eating out. The study reveals that these factors influence the preference of cuisines differently. For example, the personality of an individual has significant influence over the preference of Indian and Arabic cuisines while people who give more importance to the quality of food while eating out are more likely to prefer Indian cuisine. Furthermore, this study also reveals that as the age of people increases, their preference towards Indian cuisine increases whereas preference towards Italian cuisine decreases, while eating out. Young consumers who eat out for good food and variety of dishes are more likely to prefer Italian cuisine.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121554007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073533
Prashanth Krishnamurthy, P. Balasubramanian, Deepti Mohan
The Indian stock market is affected by many factors such as monetary policy, oil prices etc. This paper studies the relationship between Exchange rate return of Rupee-Dollar and various Stock Indices returns of India namely Nifty IT, Nifty Pharma, Nifty MNC, Nifty Commodity Index, Nifty Energy Index and Nifty Metal Index, for the time period December 2011-December 2016. The study also takes into account the volatility of returns of these indices and that of exchange rate returns to study the relationship between these two variables using Granger Causality Test. It was observed that Commodity Index return, IT index return, MNC Index return, Energy Index return, Sigma Commodity Index return and Sigma IT index return granger cause the Exchange rate return.
{"title":"Study on relationship between exchange rate return and various stock indices returns","authors":"Prashanth Krishnamurthy, P. Balasubramanian, Deepti Mohan","doi":"10.1109/ICDMAI.2017.8073533","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073533","url":null,"abstract":"The Indian stock market is affected by many factors such as monetary policy, oil prices etc. This paper studies the relationship between Exchange rate return of Rupee-Dollar and various Stock Indices returns of India namely Nifty IT, Nifty Pharma, Nifty MNC, Nifty Commodity Index, Nifty Energy Index and Nifty Metal Index, for the time period December 2011-December 2016. The study also takes into account the volatility of returns of these indices and that of exchange rate returns to study the relationship between these two variables using Granger Causality Test. It was observed that Commodity Index return, IT index return, MNC Index return, Energy Index return, Sigma Commodity Index return and Sigma IT index return granger cause the Exchange rate return.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073504
Omkar Prabhune, Pradnya Sabale, D. Sonawane, C. Prabhune
Image processing involves extraction, filtering, enhancement etc. of images using mathematical operations. Every digital image has a corresponding matrix of color and color intensities. Various mathematical operations are performed on these matrices for enhancing the corresponding image. This paper explains various image processing techniques like incorporation and extraction of digital watermark, image compression, point operations performed for enhancements, filtering techniques, specifically noise reduction in an image using singular value decomposition method.
{"title":"Image processing and matrices","authors":"Omkar Prabhune, Pradnya Sabale, D. Sonawane, C. Prabhune","doi":"10.1109/ICDMAI.2017.8073504","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073504","url":null,"abstract":"Image processing involves extraction, filtering, enhancement etc. of images using mathematical operations. Every digital image has a corresponding matrix of color and color intensities. Various mathematical operations are performed on these matrices for enhancing the corresponding image. This paper explains various image processing techniques like incorporation and extraction of digital watermark, image compression, point operations performed for enhancements, filtering techniques, specifically noise reduction in an image using singular value decomposition method.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"140 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129039966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073485
Biraja Prasad Nayak, Animesh Shaw
This article proposes the hysteresis control algorithm for the improvement of power quality by series active power filter (APF). Here, the Simulink model of series active power filter and its control technique by hysteresis PWM controller has been carried out in MATLAB SIMULINK. The voltage sag analysis and total harmonic distortion (THD) analysis are also carried out by using FFT analysis. Simulation result shows that the proposed configuration for series APF has the expected performance.
{"title":"Reduction of harmonics and voltage sag compensation by series active power filter","authors":"Biraja Prasad Nayak, Animesh Shaw","doi":"10.1109/ICDMAI.2017.8073485","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073485","url":null,"abstract":"This article proposes the hysteresis control algorithm for the improvement of power quality by series active power filter (APF). Here, the Simulink model of series active power filter and its control technique by hysteresis PWM controller has been carried out in MATLAB SIMULINK. The voltage sag analysis and total harmonic distortion (THD) analysis are also carried out by using FFT analysis. Simulation result shows that the proposed configuration for series APF has the expected performance.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116420301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073509
R. Deshmukh, B. N. Jagdale
Nowadays, Smartphone's are being more and more popular as technology is being evolve. Smartphone's are capable for providing numerous services, such as Location Aware services like GPS. They share all the location information of the user to the server. Whenever user submit any query to location aware service, those queries also carries some personal information about user. The query and information is then submitted of LBS server. Someone at server's side may use this information to make user panic. To overcome this, new collaborative approach to hide users personnal data from LBS serve is introduced. An Adversary at LBS may misuse this location information and may plan an attack. Hence Users privacy is a issues to be resolved. We address this difficult by offering a system where user will not be exposed to the LBS, that is users identity and location would be hidden from the server. By using Third Party server we will hide User from Service provider. The solution does involve not alter the LBS server architecture but assume third party servers to significantly increase users' location privacy. To enhance privacy of user, we will add registration and verification system to the model, so that only authenticated users would ask for query response. By this Registration system we will be generating ID's, through that ID's interaction between user and LBS would happen, by which LBS would never know use's original identity and from which user location queries are fired. This prototype helps to examine the effects of several constraints, such as querying rates of user and the lifespan of context information, on users' location privacy.
{"title":"Design and development of privacy preserving architecture for mobile users","authors":"R. Deshmukh, B. N. Jagdale","doi":"10.1109/ICDMAI.2017.8073509","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073509","url":null,"abstract":"Nowadays, Smartphone's are being more and more popular as technology is being evolve. Smartphone's are capable for providing numerous services, such as Location Aware services like GPS. They share all the location information of the user to the server. Whenever user submit any query to location aware service, those queries also carries some personal information about user. The query and information is then submitted of LBS server. Someone at server's side may use this information to make user panic. To overcome this, new collaborative approach to hide users personnal data from LBS serve is introduced. An Adversary at LBS may misuse this location information and may plan an attack. Hence Users privacy is a issues to be resolved. We address this difficult by offering a system where user will not be exposed to the LBS, that is users identity and location would be hidden from the server. By using Third Party server we will hide User from Service provider. The solution does involve not alter the LBS server architecture but assume third party servers to significantly increase users' location privacy. To enhance privacy of user, we will add registration and verification system to the model, so that only authenticated users would ask for query response. By this Registration system we will be generating ID's, through that ID's interaction between user and LBS would happen, by which LBS would never know use's original identity and from which user location queries are fired. This prototype helps to examine the effects of several constraints, such as querying rates of user and the lifespan of context information, on users' location privacy.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114821543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073517
Tejaswini U. Mane
The term Big Data is becoming global today. The Big data is huge amount of variety of data, and the data is increasing very rapidly according to the time. So there is need to process that data and instead of just storing that data need to extract some meaningful information or knowledge from that data applying some clustering and classification techniques of data mining. There are various era available in the Big Data so that decided the medical field first. And after that there are various diseases available to work on them or gain some knowledge or predict for help we decided the Heart disease. Heart disease is one of the disease due to that death will occurred mostly, and according to the world health organization the percentage is more for that. So Heart disease is decided for the big Data approach, and as Big Data is considered so used Hadoop Map reduce platform. For clustering Improved K-Means and for the classification purpose decision tree algorithm i.e. ID3 is used in the hybrid approach. As we know the taking second opinion is too increased, the system is very useful for the helping in prediction, basis on the some parameters like chest pain, cholesterol, age, resting Bp, Thalac and many more. Due to this system clinical decision making will be improved as well as being fast. It's also will impact on the improving the treatment process. In such way it will be very useful in the prediction of the heart disease.
{"title":"Smart heart disease prediction system using Improved K-means and ID3 on big data","authors":"Tejaswini U. Mane","doi":"10.1109/ICDMAI.2017.8073517","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073517","url":null,"abstract":"The term Big Data is becoming global today. The Big data is huge amount of variety of data, and the data is increasing very rapidly according to the time. So there is need to process that data and instead of just storing that data need to extract some meaningful information or knowledge from that data applying some clustering and classification techniques of data mining. There are various era available in the Big Data so that decided the medical field first. And after that there are various diseases available to work on them or gain some knowledge or predict for help we decided the Heart disease. Heart disease is one of the disease due to that death will occurred mostly, and according to the world health organization the percentage is more for that. So Heart disease is decided for the big Data approach, and as Big Data is considered so used Hadoop Map reduce platform. For clustering Improved K-Means and for the classification purpose decision tree algorithm i.e. ID3 is used in the hybrid approach. As we know the taking second opinion is too increased, the system is very useful for the helping in prediction, basis on the some parameters like chest pain, cholesterol, age, resting Bp, Thalac and many more. Due to this system clinical decision making will be improved as well as being fast. It's also will impact on the improving the treatment process. In such way it will be very useful in the prediction of the heart disease.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121173219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073508
Amol K. Koshti, M. Rao
This paper discusses the brief review of different multilevel inverter topologies and the introduction of control strategies used for MLI'S. In today's scenario multilevel inverter becoming popular in the industry for high voltage and medium voltage application also in the renewable energy fields. The input voltage can be obtained from dc battery, energy storage capacitors or any kind of renewable energy sources. The various topologies are, Diode clamped multilevel inverter, Flying capacitor multilevel inverter, Cascaded H-bridge converter and they can be used in AC motor drives, Uninterruptible power supply (UPS), Harmonic current compensation, static compensators. It requires a complex driving circuit to fire the switches in the circuit is the main disadvantage of the multilevel inverter.
{"title":"A brief review on multilevel inverter topologies","authors":"Amol K. Koshti, M. Rao","doi":"10.1109/ICDMAI.2017.8073508","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073508","url":null,"abstract":"This paper discusses the brief review of different multilevel inverter topologies and the introduction of control strategies used for MLI'S. In today's scenario multilevel inverter becoming popular in the industry for high voltage and medium voltage application also in the renewable energy fields. The input voltage can be obtained from dc battery, energy storage capacitors or any kind of renewable energy sources. The various topologies are, Diode clamped multilevel inverter, Flying capacitor multilevel inverter, Cascaded H-bridge converter and they can be used in AC motor drives, Uninterruptible power supply (UPS), Harmonic current compensation, static compensators. It requires a complex driving circuit to fire the switches in the circuit is the main disadvantage of the multilevel inverter.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115969839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073512
Paramita Ray, A. Chakrabarti
In recent times, people share their opinions, ideas through social networking site, electronic media etc. Different organizations always want to find public opinions about their products and services. Individual consumers also want to know the opinions from existing users before purchasing product. Sentiment analysis is the computational treatment of user's opinions, sentiments and subjectivity of text. In this paper we propose a framework for sentiment analysis using R software which can analyze sentiment of users on Twitter data using Twitter API. Our methodology involves collection of data from Twitter, its pre-processing and followed by a lexicon based approach to analyze user's sentiment.
{"title":"Twitter sentiment analysis for product review using lexicon method","authors":"Paramita Ray, A. Chakrabarti","doi":"10.1109/ICDMAI.2017.8073512","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073512","url":null,"abstract":"In recent times, people share their opinions, ideas through social networking site, electronic media etc. Different organizations always want to find public opinions about their products and services. Individual consumers also want to know the opinions from existing users before purchasing product. Sentiment analysis is the computational treatment of user's opinions, sentiments and subjectivity of text. In this paper we propose a framework for sentiment analysis using R software which can analyze sentiment of users on Twitter data using Twitter API. Our methodology involves collection of data from Twitter, its pre-processing and followed by a lexicon based approach to analyze user's sentiment.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"71 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126952014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/ICDMAI.2017.8073522
Tong Liu, Jasper Mbachu, A. Mathrani
The construction sector is a key driver of economic growth in New Zealand; however its productivity is low. Prior research has suggested that ICT (information and communication technologies) can help enhance efficiency and productivity. Currently there are a large number of smartphone apps developed for the construction industry. In this study we have conducted a preliminary investigation on the use of construction related apps and to obtain a general view on uptake of smartphone apps in the small and medium enterprise construction sector within New Zealand. Empirical data has been obtained through interviews conducted with 14 members of the New Zealand's registered master builders. Data analysis reveals that majority construction workers use smartphones (iPhone and Android) and generally have a positive attitude towards adoption of smartphone apps. However, more needs to be done to improve the visibility of apps to construction personnel. Suggestions to help the uptake of mobile apps in the New Zealand construction industry comprise conducting trainings, workshops, promotions, changing from top-down approach and providing some scenarios or examples to indicate that productivity can be improved with apps. This study provides a snapshot view of the pervasiveness of smartphone apps in the construction sector and leads to insights for conducting further research on a larger scale regarding use of construction apps.
{"title":"A preliminary investigation on use of construction apps in New Zealand","authors":"Tong Liu, Jasper Mbachu, A. Mathrani","doi":"10.1109/ICDMAI.2017.8073522","DOIUrl":"https://doi.org/10.1109/ICDMAI.2017.8073522","url":null,"abstract":"The construction sector is a key driver of economic growth in New Zealand; however its productivity is low. Prior research has suggested that ICT (information and communication technologies) can help enhance efficiency and productivity. Currently there are a large number of smartphone apps developed for the construction industry. In this study we have conducted a preliminary investigation on the use of construction related apps and to obtain a general view on uptake of smartphone apps in the small and medium enterprise construction sector within New Zealand. Empirical data has been obtained through interviews conducted with 14 members of the New Zealand's registered master builders. Data analysis reveals that majority construction workers use smartphones (iPhone and Android) and generally have a positive attitude towards adoption of smartphone apps. However, more needs to be done to improve the visibility of apps to construction personnel. Suggestions to help the uptake of mobile apps in the New Zealand construction industry comprise conducting trainings, workshops, promotions, changing from top-down approach and providing some scenarios or examples to indicate that productivity can be improved with apps. This study provides a snapshot view of the pervasiveness of smartphone apps in the construction sector and leads to insights for conducting further research on a larger scale regarding use of construction apps.","PeriodicalId":368507,"journal":{"name":"2017 International Conference on Data Management, Analytics and Innovation (ICDMAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126966189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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