مقاله انگلیسی رایگان در مورد کلان داده و شهرهای هوشمند – اسپرینگر 2017

 

مشخصات مقاله
انتشار مقاله سال 2017
تعداد صفحات مقاله انگلیسی 25 صفحه
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منتشر شده در نشریه اسپرینگر
نوع مقاله ISI
عنوان انگلیسی مقاله Big data and smart cities: a public sector organizational learning perspective
ترجمه عنوان مقاله کلان داده و شهرهای هوشمند: چشم انداز یادگیری سازمانی بخش عمومی
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مدیریت، شهرسازی، معماری، فناوری اطلاعات
گرایش های مرتبط مدیریت فناوری اطلاعات، سیستم های اطلاعاتی پیشرفته، طراحی شهری
مجله سیستم های اطلاعاتی و مدیریت تجارت الکترونیکی – Information Systems and e-Business Management
دانشگاه Department of Business Management – Glasgow Caledonian University –  UK
کلمات کلیدی کلان داده، شهرهای هوشمند، بخش عمومی، یادگیری سازمانی
کلمات کلیدی انگلیسی Big data, Smart cities, Public sector, Organizational learning
کد محصول E7375
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1 Introduction

Big data is poised to change the way we live and work (Manyika et al. 2011; MayerScho¨nberger and Cukier 2013). The implications of deploying big data for work, such as in smart city initiatives, has impacted the way organizations operate. Organisations have now had to redefine and construct new models to adapt to this disruptive technology. George et al. (2014) stressed that even though the term big data has become a common business parlance, there has been little research in management scholarly circles. Especially those that address ‘‘the challenges of using such tools—or, better yet, that explores the promise and opportunities for new theories and practices that big data might bring about’’ (p. 321). There has also been little organizational research that has explored the learning experiences in the advent of such new technologies. Therefore, this research explores the learning processes involved in how public organizations have been able to embrace big data in providing smart city solutions. The smart city concept is widely perceived as a means of solving urban issues through the integration of information technology (IT) with the city’s infrastructure (Caragliu et al. 2011). Big data has, in turn, become an integral part of this phenomenon. As this study is time-sensitive, there are difficulties defining the constituent parts of the research context: namely, big data and a smart city. As such, working definitions of concepts are constructed for this paper. Therefore, big data is the generation of infinite, unstructured data from different sources that possess diverse characteristics. On the other, urban issues are regarded as wicked problems—intractable problems (Bettencourt 2014; Rittel and Webber 1973). Whereas, a smart city is one where ‘‘investments in human and social capital and traditional (transport) and modern (ICT) communication infrastructure fuel sustainable economic growth and a high quality of life, with a wise management of natural resources, through participatory governance’’ (Caragliu et al. 2011, p. 70). These definitions are appropriate because they capture the current state-of-thescience and help define the boundaries of this research. Invariably, the smartness of a city has been linked to how it deploys and integrates big data as a tool used in the delivery and provision of services (Batty 2013; Kitchin 2014). The data used in smart city initiatives are usually public data that can be accessed, in some instances, under restrictions to protect privacy, for example in areas energy use, healthcare and transportation (George et al. 2014). Organisations have found themselves at the centre of a data deluge. So far, Tambe (2014) has found out that firms’ that invest in big data technologies have a higher productivity are than those that invest less. Whereas, Popovicˇ et al. (2016) point that the use of big data enhances decision making and business performance in manufacturing. To the best of our knowledge, we have found no research that has explored how manager’s public or private organizations learned to deploy the use of big data to carry out organisational tasks. We look to research in organizational learning (OL) to consider how organizations exploit and experience using big data, in this case for carrying out smart city initiatives. For consistency with the literature and clarity in presentation, we adapt the definition of organisational learning to be the process of building capacity for effective organizational action through knowledge and understanding (Burnes et al. 2003; Carroll and Edmondson 2002; Elkjaer 2004). We argue that given the fast moving pace and the novelty of such concepts, organizational efforts to understand what they are, what they can do, and the infrastructure needed to exploit and manage it from a public sector’s perspective, so far, are based on an organizations’ ability to embed acquired knowledge.