Abstract

Abstract
The aim of the present study is to analyze brand resonance measures to assess reliability, dimensionality and validity using existing models of brand resonance. This study is based on a mixed approach of research methodology, using qualitative and quantitative methods. In the qualitative approach, we use expert interview and focus group discussion tools. In the quantitative approach, a corporate survey was conducted and 560 responses were collected through a structured questionnaire. The analysis is performed using statistical scaling tools such as Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). This study initiated scale extraction and operationalization processes for 72 observed variables to measure nine latent variables and obtained 34 statistically extracted observed variables. The study provides a reliable and validated means to measure brand resonance constructs. The study develops a brand resonance scale, which can help brand managers to measure consumers’ levels of brand resonance, in order to describe the strength of the bond of their consumer with their brand(s). This study develops empirically extracted measures of brand resonance, making it distinctive in the branding literature. The study also ensures all important aspects of measurement scale, such as validity and reliability. © 2019 International Management Institute, New Delhi.

Abstract

Abstract

Abstract
A new decentralised demand response (DR) model relying on bi-directional communications is developed in this study. In this model, each user is considered as an agent that submits its bids according to the consumption urgency and a set of parameters defined by a reinforcement learning algorithm called Q-learning. The bids are sent to a local DR market, which is responsible for communicating all bids to the wholesale market and the system operator (SO), reporting to the customers after determining the local DR market clearing price. From local markets' viewpoint, the goal is to maximise social welfare. Four DR levels are considered to evaluate the effect of different DR portions in the cost of the electricity purchase. The outcomes are compared with the ones achieved from a centralised approach (aggregation-based model) as well as an uncontrolled method. Numerical studies prove that the proposed decentralised model remarkably drops the electricity cost compare to the uncontrolled method, being nearly as optimal as a centralised approach.

Abstract