دانلود رایگان مقاله انگلیسی داده های بزرگ و شهرهای هوشمند: چشم انداز یادگیری سازمانی بخش عمومی - اشپرینگر 2017

Abstract

Public sector organizations (city authorities) have begun to explore ways to exploit big data to provide smarter solutions for cities. The way organizations learn to use new forms of technology has been widely researched. However, many public sector organisations have found themselves in new territory in trying to deploy and integrate this new form of technology (big data) to another fast moving and relatively new concept (smart city). This paper is a cross-sectional scoping study—from two UK smart city initiatives—on the learning processes experienced by elite (top management) stakeholders in the advent and adoption of these two novel concepts. The findings are an experiential narrative account on learning to exploit big data to address issues by developing solutions through smart city initiatives. The findings revealed a set of moves in relation to the exploration and exploitation of big data through smart city initiatives: (a) knowledge finding; (b) knowledge reframing; (c) inter-organization collaborations and (d) ex-post evaluations. Even though this is a time-sensitive scoping study it gives an account on a current state-of-play on the use of big data in public sector organizations for creating smarter cities. This study has implications for practitioners in the smart city domain and contributes to academia by operationalizing and adapting Crossan et al’s (Acad Manag Rev 24(3): 522–537, 1999) 4I model on organizational learning.

4 Discussion

The advent of big data and its use for addressing urban issues—in the form of smart cities—reveals the dynamics and complexities of adopting these new and fastmoving concepts. The study particularly demonstrates an iterative (feedback and feed forward) process that forms a learning eco-system within organizations. With scant research available on the use of big data in (public) organizations, this research sets the groundwork for more exploratory research into the use of big data. Also, as city councils want to make their urban areas smarter, our foray into this study was informed by the literature on existing OL literature, especially those that had focused on public sector learning (Rashman et al. 2009). By using a smart city context, this study points out the learning points of using big data from a public sector perspective. The learning experiences from these public sector organizations unearths experiences public sector organizations have faced in trying to adopt a big data approach to problem-solving. The findings reveal that organizations that adopt the key learning points around the use of big data have the ability to use big data to reframe problems facing their cities; use data-driven mechanisms to build a knowledge base for problems facing their city; work collaboratively with partner organizations across various sectors and, most importantly, reflect on the learning phases they had gone through.

The conceptual model in Fig. 2 is an adaptation to the 4I model developed by Crossan et al. (1999); based on four broad actions: intuiting, interpreting, integrating and institutionalizing activities across the organizational levels. The difference, however, is that theirs cuts across all organizational levels but our adaptation does not. Our adaption is also different from past studies that have adopted the 4I model, such as Stevens & Dimitriadis (2004), which have been longitudinal and multilevel. Still, this research reveals that organizations can intuit, interpret, integrate and institutionalize knowledge.