Show simple item record

contributor authorRobert Wilhelm Siegfried Ruhlandt
contributor authorRaymond Levitt
contributor authorRishee Jain
contributor authorDaniel Hall
date accessioned2022-01-30T19:50:51Z
date available2022-01-30T19:50:51Z
date issued2020
identifier other%28ASCE%29ME.1943-5479.0000762.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4266077
description abstractData and analytics can be a facilitator and driver of growth for cities. Their significance will likely continue to grow and be amplified by new technological developments. However, research on cities’ utilization of data and analytics has been comparatively vague and imprecise and requires a more holistic and systematic perspective. Therefore, this study examines the potential condition variables that could drive cities’ utilization of data and analytics, employing a multimethod approach that includes comparative case studies, content analysis, and the Delphi method. This hybrid research approach allows the authors to combine the strengths of various research methods and is, therefore, among the first that uses this kind of approach in such a research context. The authors identify several indicators or drivers (structures, processes, leadership, strategy, culture, data infrastructure, data governance, skills, training, capacities, budgets) that are essential to build a theory around a city’s utilization of data and analytics. In addition, a conceptual model classifies these potential drivers into six broad (superordinate) categories: organization, procedures, direction, data, competencies, and resources. For scholars, the study contributes to the growing body of knowledge by identifying potential drivers of cities’ utilization of data and analytics. For practitioners, the study provides insights through the formation of a standardization tool (appropriate measurement techniques for each potential driver) for assessing cities’ data and analytics utilization. In addition, the authors suggest directions for further research.
publisherASCE
titleDrivers of Data and Analytics Utilization within (Smart) Cities: A Multimethod Approach
typeJournal Paper
journal volume36
journal issue2
journal titleJournal of Management in Engineering
identifier doi10.1061/(ASCE)ME.1943-5479.0000762
page04019050
treeJournal of Management in Engineering:;2020:;Volume ( 036 ):;issue: 002
contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record