A strategic model-based of micro-moment data in smart cities especially internet of things

Document Type : Research Paper


1 Department of Management, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran

2 Department of Management, Supreme National Defense University, Tehran, Iran


Many industry leaders predict that the industrial Internet will create unprecedented levels of growth and productivity over the coming decades. Business leaders, governments, academic environments, and technology vendors are working hard together to realize and restrain this powerful potential. In this research, the combined method has been used. In the qualitative part, the foundation data method or grounded theory with a systematic approach which attributed to Strauss and Corbin has been used for data analysis and has been designed with three open, axial and selective coding techniques in Maxqda model software. Then, the questionnaire was designed in 6 dimensions: causal, axial phenomenon, prevailing context, intervening conditions and consequences in 50 items to confirm the dimensions, components and indicators. The statistical population is consist of 35 managers and basic technology senior experts in the Internet of Things (IOT) field, marketing and information technology experts who have been selected by Snow Ball method (chain reference) to the theoretical saturation limit. In the quantitative part, after identifying the relevant dimensions, components and indicators, the questionnaire was provided to managers and experts. The results were confirmed by independent t-test. Prioritization of dimensions and components has been done by AHP technique. Reliability of interviews with Cohen's Kappa coefficient and inter-rater reliability method, content validity of the questionnaire using content validity ratio (CVR), content validity index (CVI), apparent validity with item impact scores and reliability with Cronbach's alpha and halving method has been approved.


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Volume 12, Special Issue
December 2021
Pages 231-242
  • Receive Date: 10 December 2020
  • Revise Date: 09 March 2021
  • Accept Date: 04 April 2021