Consumers' willingness to pay for ethical attributes

Purpose: In recent years, there has been a big increase in the use of ethical attributes as marketing appeals. This paper examines consumers’ willingness to pay for three selected ethical attributes, namely ‘Organic’, ‘Recyclable Packaging’ and ‘Fairtrade’ in monetary terms. Design/Methodology/Approach: A modified choice-based experimental design with manipulation of the key constructs was used to estimate the mean value of how much consumers are willing to pay for the selected attributes attached to a box of premium chocolates. The results are based on the responses of a total of 208 consumers. Findings: Of the three attributes, ‘Recyclable Packaging’ has the strongest influence on the purchase decision, although this attribute generates the least additional value. The aggregated result shows that although consumers are willing to pay more for the product with ethical attributes than the one that is without, still around a half of them are not willing to pay more. In terms of demographics, the results show no significant differences between the two genders or different age groups in their willingness to pay for ethical attributes. As might be expected, willingness to pay was correlated with the level of consciousness of the ethical attributes. Originality/Value: The findings of this study help management to think practically about the value consumers willing to pay for the selected attributes. The results show a significant synergy in a combination of ethical attributes in products.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

SCADA House Intelligent Management for Energy Efficiency Analysis in Domestic Consumers

The implementation of smart homes allows the domestic consumer to be an active player in the context of the Smart Grid (SG). This paper presents an intelligent house management system that is being developed by the authors to manage, in real time, the power consumption, the micro generation system, the charge and discharge of the electric or plug-in hybrid vehicles, and the participation in Demand Response (DR) programs. The paper proposes a method for the energy efficiency analysis of a domestic consumer using the SCADA House Intelligent Management (SHIM) system. The main goal of the present paper is to demonstrate the economic benefits of the implemented method. The case study considers the consumption data of some real cases of Portuguese house consumption over 30 days of June of 2012, the Portuguese real energy price, the implementation of the power limits at different times of the day and the economic benefits analysis.

Defining Electricity Tariffs Using the Knowledge About the Consumers Profiles in ELECON Project

The increasing importance of the integration of distributed generation and demand response in the power systems operation and planning, namely at lower voltage levels of distribution networks and in the competitive environment of electricity markets, leads us to the concept of smart grids. In both traditional and smart grid operation, non-technical losses are a great economic concern, which can be addressed. In this context, the ELECON project addresses the use of demand response contributions to the identification of non-technical losses. The present paper proposes a methodology to be used by Virtual Power Players (VPPs), which are entities able to aggregate distributed small-size resources, aiming to define the best electricity tariffs for several, clusters of consumers. A case study based on real consumption data demonstrates the application of the proposed methodology.

Consumers Performance Evaluation of the Participation in Demand Response Programs Using Baseline Methods

Demand response has gain increasing importance in the context of competitive electricity markets environment. The use of demand resources is also advantageous in the context of smart grid operation. In addition to the need of new business models for integrating demand response, adequate methods are necessary for an accurate determination of the consumers’ performance evaluation after the participation in a demand response event. The present paper makes a comparison between some of the existing baseline methods related to the consumers’ performance evaluation, comparing the results obtained with these methods and also with a method proposed by the authors of the paper. A case study demonstrates the application of the referred methods to real consumption data belonging to a consumer connected to a distribution network.

Demand Response Programs Definition Using Demand Price Elasticity to Define Consumers Aggregation for an Improved Remuneration Structure

The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers’ participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers’ scenario.

The dynamics of brand loyalty across a consumer’s lifetime

This project studies the Portuguese female fashion market. We intend to determine patterns of consumer brand loyalty across brands and ages. By interviewing 8 young adults and surveying 125 teens and 87 adults, we found that brands’ segmentation by usage per age segment is related with differentiation in brand loyalty and peer pressure. We also found that teens have higher attitudinal brand loyalty while adults have higher behavioral loyalty. Moreover, brand loyalty in teens is more susceptible to peer pressure. The results imply that customer relationship management strategies should be differentiated according to age segment. We also derive marketing implications with a focus on each brand’s loyalty profile.

Are the L'oreal hair care brands currently operating in the Kenyan mass market adequately positioned and adapted to the Kenyan consumers?: A recommendation to the new L'oreal East Africa Office concerning the hair care brand positioning and portfolio in Kenya

NSBE - UNL

The influence of price changes on consumers' purchase decisions

The development of an effective pricing strategy requires the acquaintance of consumers’ price perception as well as the range of elements that influence the price sensitivity. This paper analyses the relationships between product features, individual characteristics and the level of price increase/decrease that induces the consumers to change their purchase decisions. The results of a dedicated survey show, that price sensitivity, individual preferences, type of product and direction of price change and individual characteristics of consumers (gender, age, professional situation) have a significant impact on a threshold at which people are willing to choose the less attractive, but cheaper alternative to their favorite product or give up the variety in consumption. From a consumer behavior perspective, these findings play a fundamental role in pricing.

The role of humor in television advertisement: A study regarding Portuguese consumers’ emotions and reactions

The purpose of this study is to explore the humorous side of television advertisement and its impact on Portuguese consumers’ hearts, minds and wallets. Both qualitative (through in-depth interviews) and quantitative (through an on-line survey and subsequent statistical data analysis) methods were used, guaranteeing a more consistent, strong and valid research. Twenty-five interviews with randomly chosen consumers were conducted face-to-face and three interviews via e-mail with marketers and television advertisers were performed in order to explore profoundly the subject. Moreover, 360 people have answered the on-line survey. Through the analysis of the data collected humor perception was found to be positively correlated with persuasion and intention to purchase the product; intention to share the advert; message comprehension; product liking and development of positive feelings towards the brand and brand credibility variables. The main implication of these findings relies on the fact that humor in advertising is able to boost its effectiveness.