8 research outputs found
Big Data and Human Resource Management Nexus: A Review and Future Direction
Get PDFDramatic technological advancements, heavy reliance on data, the introduction of advanced information communication technologies, electronic business and high-end computing capacity necessitated the importance of big data application in organizations. Despite the increasing importance of big data, however, organizations have faced plenty of challenges. Thus, the reviewer aimed to identify the roles of big data for Human Resource Management (HRM), problems faced by HR professionals in using big data and provide solutions to the problems faced. In doing so, the reviewer collected research papers between 2014 and 2016 with the help of âGoogle scholarâ search engine using search words âbig dataâ, âHR analyticsâ and âHRMâ to come up with 28 relevant articles out of 35 journal articles. The review indicated that big data proved itself to be a very useful in recruitment, training, pay-performance fit, and career management among others. With regard to problems of big data use in HRM authors indicated several issues including but not limited to; characteristics of big data, difficulty in understanding the concept of big data, deciding over what data are generated and collected, issues of privacy, ethical considerations relevant to mining such data, high infrastructure costs, lack of the skills, knowledge and insight to ask the right questions of the HR data and functional silos in the organization whereby HR and organizational leaders fail to strengthen the capacity of experts in combining HR related data with other determinants of productivity and performance. The reviewer suggests that big data and its scope should be well defined; distinctive characteristics and types of big data should be understood with specific reference to HRM; and problems/challenges should properly be addressed through the establishment of joint team of HRM and big data experts. Finally, both the academia and practitioners should embrace the new research paradigm that focuses on the proper alignment of big data with HRM for better organizational success and researchers should produce studies that show techniques of data mining as well as big data analytics in relation to HRM practices. Keywords: Big data, HRM, HR analytics
BIG DATA A BIG DEAL FOR CAPITAL MARKET COMPANIES IN THEIR TRANSFORMATION PROCESS?
Get PDFAbstract The following article discusses the importance of using big data, especially in the operation of capital market companies, both in terms of benefits and potential risks. Given the growing dynamic business environment, capital market companies have to transform their operations in order to accommodate the raising demands. Fast business decision making is of particular importance in this process. Structured use of data plays a major role in decision-making, especially as the amount of large digital data in the modern world grows at an unprecedented rate. Author of the article focuses on the statistical and econometric techniques required for the analysis of big data. The article also highlights some use cases and the growing interest of capital market companies in introducing big data analytical technologies and the relevant challenges and benefits. In addition, using so-called "Simpsonâs Reversal Paradox" author explains that using big data and digging deep into details might be counterproductive and lead to loss of global picture and wrong decision-making
A Systematic Review for the Challenges Related to the Implementation of Building Information Modelling, Big Data Analytics and Internet of Things (BBI) in the Construction Sector
Get PDFUnder scrutiny for the past several years, the adoption of Building Information Modelling (BIM), Big Data Analytics (BDA) and Internet of Things (IoT) (together also known as BBI) is yet to grow significantly in the construction industry. The industry itself is realising the complexity and challenges which admittedly inhibit BBI implementation. The identification of these challenges is an imperative precondition for successful implementation of BBI. Even though there is a paucity of empirical data in this area, a notable body of research has reported such challenges which are the target consideration of this paper. However, no study has comprehensively reviewed, and synthesized existing research on the basis of treating BBI implementation as an integrated process and viewing these challenges as the cause for laggard manifestations, which underpins the originality and value of this study. To bridge this gap in literature, this paper primarily undertakes a critical systematic review of research around challenges related to BBI implementation. It emphasises a variety of important challenges inter-alia, skills and training needs, level of interoperability, infrastructure associated costs, data security, privacy, data ownership and supply chain concerns. This synthesis shows that BBI implementation is complex and challenging, and suggests that the industry as a whole need to take immediate actions. The need for more concerted research efforts to bridge the gaps are also identified. Finally, the paper proffers recommendations for managers and workers, which have social, technological, and economic capability and capacity dimensions
What do we know about the big data researches? A systematic review from 2011 to 2017
Get PDFBig data are defined as a new phenomenon that can be novel step for improving social life and business condition. Analysing the big dataâs researches to extract insights by systematic literature review is the main objective of this research. For synthesis systematically, data from 123 articles are extracted and kinds of studies that were usually done on big data area are investigated. The Systematic Review showed: the most studies were published in 2014, also the main journal that published big dataâs article was âBig Data Researchâ and country with highest investigate about big data were âUnited State and Chinaâ. Beside, most researches were done with analytic background. The main research method was experimental and major research type was case study. Our study proved that the majority of researches carried out around big data focused on data management, and most of them identify âvolume and varietyâ of as significant challenges of big data. Likewise, âbusiness analyticsâ was described in the major benefits
ZHVILLIMI DHE EVOLUIMI I BIG DATA
Get PDFNĂ« ditĂ«t e sotme ne po pĂ«rjetojmĂ« njĂ« pĂ«rmbytje tĂ« madhe nga tĂ« dhĂ«nat, si rezultat jo vetĂ«m i internetit dhe kompjuterizimit tĂ« shoqĂ«risĂ« sonĂ«, mirĂ«po edhe si pasojĂ« e grumbullimit dhe ruajtjes sĂ« tĂ« dhĂ«nave tĂ« papĂ«rballueshme dhe tĂ« fuqishme nĂ«pĂ«r pajisje. KĂ«to tĂ« dhĂ«na janĂ« nĂ« rritje eksplozive, si nĂ« madhĂ«si ashtu edhe nĂ« formĂ«, tĂ« cilat njĂ«herit paraqesin njĂ« sfidĂ« themelore pĂ«r analiza tĂ« mĂ«dha tĂ« tĂ« dhĂ«nave. Kjo rritje e shpejtĂ« pritet tĂ« vazhdojĂ« dhe statistikat tregojnĂ« numĂ«r edhe mĂ« tĂ« lartĂ« tĂ« kĂ«saj rritje nĂ« vitet nĂ« vazhdim. TĂ« dhĂ«nat vijnĂ« nga kudo - nga sensorĂ« nĂ« telefonat mobil dhe makina, nga transaksionet nĂ« internet dhe blerjet me kartĂ« krediti, nga pyetjet e kĂ«rkimit nĂ« shfletues tĂ« internetit, nga emailet, rrjedhat e klikimeve dhe shkrimet, por edhe nga tĂ« dhĂ«nat shĂ«ndetĂ«sore, rrjetet elektrike, rrugĂ«t, urat dhe pozicionimi global i satelitĂ«ve. Me fjalĂ« tĂ« tjera, çdo gjĂ« qĂ« bĂ«jmĂ« dhe çdo gjĂ« qĂ« ndodh nĂ« botĂ« Ă«shtĂ« e regjistruar. Pra tĂ« dhĂ«nat janĂ« rritur nĂ« njĂ« vĂ«llim tĂ« madh, pĂ«rmbajnĂ« variacione tĂ« ndryshme dhe janĂ« prodhuar aq shpejt sa qĂ« me kĂ«tĂ« rast Ă«shtĂ« krijuar njĂ« term i ri i quajtur âBig Dataâ (âTĂ« dhĂ«nat e mĂ«dhaâ). Mbi kĂ«tĂ« term edhe Ă«shtĂ« ndĂ«rtuar punimi i cili do tĂ« shtjellojĂ« tĂ« dhĂ«nat e mĂ«dha nĂ« pĂ«rgjithĂ«si dhe njĂ«kohĂ«sisht do tĂ« paraqes rezultatet mbi funksionalitetin dhe performancĂ«n nĂ« praktikĂ« tĂ« veglave pĂ«r menaxhim me tĂ« dhĂ«na tĂ« mĂ«dha
Explaining the Big Data adoption decision in Small and Medium Sized Enterprises: Cape Town case studies
Get PDFProblem Statement: Small and Medium-Sized Enterprises (SMEs) play an integral role in the economy of developed and developing countries. SMEs are constantly searching for innovative technologies that will not only reduce their overhead costs but also improve product development, customer relations and profitability. Literature has revealed that some SMEs around the world have incorporated a fairly new technology called Big Data to achieve higher levels of operational efficiency. Therefore, it is interesting to observe the reasons why some organizations in developing countries such as South Africa are not adopting this technology as compared to other developed countries. A large portion of the available literature revealed that there isa general lack of in-depth information and understanding of Big Data amongst SMEs in developing countries such as South Africa. The main objective of this study is to explain the factors that SMEs consider during the Big Data decision process. Purpose of the study: This research study aimed to identify the factors that South African SMEs consider as important in their decision-making process when it comes to the adoption of BigData. The researcher used the conceptual framework proposed by Frambach and Schillewaert to derive an updated and adapted conceptual framework that explained the factors that SMEs consider when adopting Big Data. Research methodology: SMEs located in the Western Province of South Africa were chosen as the case studies. The interpretive research philosophy formed the basis of this research. Additionally, the nature of the phenomenon being investigated deemed it appropriate that the qualitative research method and research design be applied to this thesis. Due to constraints such as limited time and financial resources this was a cross-sectional study. The research strategy in this study was multiple in-depth case studies. The qualitative approach was deemed appropriate for this study. The researcher used two methods to collect data, namely, the primary research method and the secondary research method. The primary research method enabled the researcher to obtain rich data that could assist in answering the primary research questions, whilst the secondary research method included documents which supplemented the primary data collected. Data was analyzed using the NVivo software provided by the University of Cape Town. Key Findings: The findings suggest that the process that influences the decision to adopt Big Data by SMEs follows a three-step approach namely: 1.) Awareness, 2.) Consideration, 3.) Intention. This indicates that for Big Data to be adopted by SMEs there must be organizational readiness to go through the process. This study identified the main intention for SMEs to adopt Big Data is to ensure operational stability. Improved operational efficiency was identified as the supporting sub-theme. This study has raised awareness about the process that SMEs, academic researchers, IT practitioners and government need to place emphasis on to improve the adoption of Big Data by SMEs. Furthermore, this study has raised awareness about the opportunities and challenges that SMEs, academic researchers, IT practitioners and government need to place emphasis on to improve the adoption of Big Data by SMEs. Value of the study: The study adds value in both academia and the business industry as it provides more insight into the factors that SMEs consider in the Big Data adoption decision
