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This paper aims to explore how home economists, employed by the Good Housekeeping Institute, may have influenced the use of principles from the home economics movement in advertising appeals for electric appliances.

A content analysis of more than 400 print advertisements from Good Housekeeping magazine, from 1916 to 1929, was conducted to determine whether manufacturers used appeals derived from the home economics movement in their advertising. Then, the Good Housekeeping Institute’s history is explored to suggest how its relationship with manufacturers may have resulted in the use of the home economics movement’s principles in advertising appeals for electric appliances.

The content analysis shows that principles of the home economics movement appeared in advertising appeals for electric appliances in advertisements placed in Good Housekeeping magazine during the period studied. Through its unique relationships with electric appliance manufacturers, the Good Housekeeping Institute seems to have taught manufacturers how to position electric appliances by incorporating the principles of the home economics movement in their advertising appeals.

This research demonstrates how a commercial organization successfully navigated its relationships with manufacturers and consumers for mutual benefit.

This work is the first to link the Good Housekeeping Institute’s work with manufacturers to its influence on advertising appeals. This work also expands understanding of the influence of women on marketing practice. Existing literature on women’s publications is also broadened by analyzing Good Housekeeping, rather than the more frequently studied Ladies’ Home Journal.

Some of the major concerns since the implementation of smart meters (prepaid meters) in some parts of Ghana is how electricity consumers have benefited from data obtained from these meters by providing important statistics on electricity-saving advice; this is one of the key demand-side management methods for achieving load reduction in residential homes. Appliance shifting techniques have proved to be an effective demand response strategy in load reduction. The purpose of this paper is therefore to help consumers of electricity understand when and how they can shift some appliances from peak to off-peak and vice versa.

The research uses an analysis technique of Richardson et al. (2010). In their survey on time-of-use surveys to determine the usage of electricity in households as far as appliance shifting was concerned, this study allowed for the assessment of how the occupants’ daily activities in households affect residential electricity consumption. Fell et al. (2014) modeled an aggregate of electricity demand using different appliances (n) in the household. The data for the peak time used in this study were identified from 05:00 to 08:00 and 17:00 to 21:00 for testing the load shifting algorithms, and the off-peak times were pecked from 10:00 to 16:00 and 23:00. This study technique used load management considering real-time scheduling for peak levels in the selected homes. The household devices are modeled in terms of controlled parameters. Using this study’s time-triggered loads on refrigerators and air conditioning systems, the findings suggested that peak loads can be reduced to 45% as a means of maintaining the simultaneous quality of service. To minimize peak loads to around 35% or more, Chaiwongsa and Wongwises (2020) have indicated that room air conditioning and refrigerator loads are simpler to move compared to other household appliances such as cooking appliances. Yet in conclusion, this study made a strong case that a decrease in household peak demand for electricity is primarily contingent on improvements in human behavior.

This study has shown that appliance load shifting is a very good way of reducing electrical consumption in residential homes. The comparative performance shows a moderate reduction of 1% in load as was found in the work done by Laicaine (2014). The results, however, indicate that load shifting to a large extent can be achieved by consumer behavioral change. The main response to this study is to advise policymakers in Ghana to develop the appropriate demand response and consumer education towards the general reduction in electrical load in domestic households. The difficulty, however, is how to get the attention of consumer’s on how to start using appliances with less load at peak and also shift some appliances from off-peak times. By increasing consumer knowledge and participation in demand response, it is possible to achieve more efficiency and flexibility in load reduction. The findings were benchmarked with existing comparison studies but may benefit from the potential production of structured references. However, the findings show that load shifting can only be done by modifying consumer actions.

It should be remembered that this study showed that the use of appliances shifting in residential homes results in load reduction benefits for customers, expressed as savings in electricity prices. The next step will be to build on this cost/benefit study to explain and measure how these reductions transform into net consumer gains for all Ghanaian households.

Load shifting will include load controllers in the future, which would automatically handle electricity consumption from various appliances in the home. Based on the device and user needs, the controllers can prioritize loads and appliance usage. The algorithms that underpin automatic load controllers will include knowledge about the behaviors of groups of end users. The results on the time dependency of activities may theoretically inform the algorithms of automatic demand controllers.

This paper addresses an important need for the country in the midst of finding solutions to an unending energy crisis. This paper presents demand response to the Ghanaian electricity consumer as a means to help in the reduction of load in residential homes. This is a novel research as no one has at yet carried out any research in this direction in Ghana. This paper has some new information to offer in the field of demand in household electricity consumption.

Under such circumstances, how to assign the highest priority for future products which will create the greatest value will be the key success factor for a product planning model. The purpose of this study is to construct an improved planning model for new products based on the theoretical structures of technology roadmaps and patent analysis.

This study takes the perspective of a product planning strategy, using technology roadmap developed by Institute of Manufacturing Technology of the University of Cambridge, combining with scenario planning and patent analysis. The main body of the proposed model is the technology roadmap of the product. Through patent analysis, the technology roadmap was integrated into the hierarchical execution of product planning to improve the disadvantages of the original technology roadmap and thereby clarify the content of the implemented procedure. With the planning of digital home products in a large household appliance manufacturer in China as a case study, the feasibility of the proposed model was verified.

The improved planning model for new products comprised five planning phases: market scenario planning, product feature analysis, technological development analysis, patent combination analysis, and resource allocation. A matrix corresponding to product planning was established. The case study is to find out the developing trends in next‐generation product features in six different scenarios of digital home for M, a home appliance manufacturer. There are five steps of the product planning model. The product planning model provides enterprises with integrated information from market demand, technology as well as patents. At the same time, it is easy to maintain and reproduce. The authors expect the model to make a contribution to practical product planning.

This model should become an essential prediction tool for enterprises developing new products and can assist in decision‐making and strategic implementation.

Power management in households has become the periodic issue for electric suppliers and household occupants. The number of electronic appliances is increasing day by day in every home with upcoming technology. So, it is becoming difficult for the energy suppliers to predict the power consumption for households at the appliance level. Power consumption in households depends on various factors such as building types, demographics, weather conditions and behavioral aspect. An uncertainty related to the usage of appliances in homes makes the prediction of power difficult. Hence, there is a need to study the usage patterns of the households appliances for predicting the power effectively.

Principal component analysis was performed for dimensionality reduction and for finding the hidden patterns to provide data in clusters. Then, these clusters were further being integrated with climate variables such as temperature, visibility and humidity. Finally, power has been predicted according to climate using regression-based machine learning models.

Power prediction was done based on different climatic conditions for electronic appliances in the residential sector. Different machine learning algorithms were implemented, and the result was compared with the existing work.

This will benefit the society as a whole as it will help to reduce the power consumption and the electricity bills of the house. It will also be helpful in the reduction of the greenhouse gas emission.

The proposed work has been compared with the existing work to validate the current work. The work will be useful to energy suppliers as it will help them to predict the next day power supply to the households. It will be useful for the occupants of the households to complete their daily activities without any hindrance.

The purpose of this study is to predict the antecedents of consumers' purchase intention of energy-efficient home appliances. This study incorporated two additional constructs (knowledge of eco-labels and knowledge of eco-labels) in the model of the theory of planned behavior. Consumers' enhanced trust for energy-efficient products is crucial to purchase intention. The second construct is consumers' knowledge of eco-labels. Knowledge of eco-labels would help to assess consumers' tendency toward environmental problems and intention to purchase energy-efficient home appliances.

This study used a quantitative approach using a survey (questionnaire) method to collect data of respondents. Non-probability quota based on age and convenience sampling techniques were employed to select the participants of this study.

The findings of the study revealed that consumer knowledge of eco-labels, green trust, subjective norm, attitude and perceived behavioral control have positive influence on purchase intention of energy-efficient home appliances.

Eco-labels are served as a marketing tool to distinguish producer's products from others. Prior studies have only focused on consumers' general knowledge. This study helps marketers to understand and design strategies to generate more value for green consumers. This study also contributes to the literature on green marketing by employing the theory of planned behavior.

The COVID-19 pandemic has caused a dramatic impact on energy supply and demand. It is vital to understand households’ behaviour with regard to energy, particularly during the pandemic, to deploy future sustainable energy systems. This study aims to investigate the nexus of Malaysian households’ energy consumption behaviour in relation to various electrical appliances, their energy-saving appliance purchasing behaviour and their current possession of energy-saving appliances during the pandemic, especially during the lockdown period, from the perspective of the energy cultures framework.

The partial least squares structural equation modelling technique was used to test hypothesised relationships based on the 1,485 pieces of household data collected using an online and physical survey during the lockdown period in Malaysia.

The energy-saving behaviour cultivated due to the impact of the COVID-19 pandemic led to residential customers’ intentions to purchase energy-saving appliances which subsequently led to their current possession of energy-saving appliances. Indeed, energy-saving behaviours in the kitchen, entertainment, office, home lighting and cooling appliances have more than 77.4% influence on their purchasing behaviour. The consumer’s purchase behaviour for energy-saving appliances has a significant, partially mediating influence on the energy-saving behaviour of various electrical appliances and the consumers’ current possession of energy-saving appliances.

This study could be enhanced by improving the sample using a higher-income group and involving other parts of Malaysia such as the southern region. The findings do extend the energy cultures framework by demonstrating the mediating role of households’ energy-saving appliance purchasing behaviour on the relationship between their energy consumption behaviour in relation to various electrical appliances and their current possession of energy-saving appliances.

The results of this study will help develop future action plans for transitioning to energy-saving appliance practices.

This paper examines the effects of the COVID-19 pandemic on future energy efficiency practices in developing countries from the perspective of the energy cultures framework.

This study examines the impact of consumer-perceived value (CPV) dimensions such as product quality, price fairness, brand prestige and brand positioning on brand attitude and loyalty for electronic home appliance brands in an emerging market. It also explores the moderating effect of perceived store image on the relationship between brand attitude and loyalty.

This study proposes an integrated model based on consumption values and the value-attitude-behavior (V-A-B) framework. Survey data from 209 Bangladeshi consumers of electronic home appliances were used to test the model. Covariance-based structural equation modeling (CB-SEM) and PROCESS macro were employed to test the hypotheses.

This research underscores the importance of CPV dimensions, such as product quality, price fairness, brand prestige and positioning, in predicting brand loyalty through brand attitude. Store image moderates the link between brand attitude and loyalty, with a stronger relationship when store image is high and a weaker relationship when it is low.

This study broadens marketing and consumption value theory by investigating brand prestige and positioning in the V-A-B framework in the emerging market. This is the first study to use perceived store image to moderate the relationship between brand attitude and loyalty.

Electricity utilization at electricity peak hour may differ from every single administration region, for example, mechanical region, business territory and residential zone. This paper introduces a demand-side load management (DSM) strategy, which is one of the utilization of smart grid (SG) that is fit for controlling loads inside the residential working so that the client fulfillment is augmented at least expense.

In this paper, a heuristic algorithms-based energy management controller is intended for a residential region in a SG. Here, Antlion Optimization technique is used for DSM techniques such as load shifting, peak clipping, and valley filling in the residential sectors for 24 h with the help of stochastic function to determine the detection of random distribution of the load.

This proposed algorithm offered the greatest fulfillment and least expense caused by the consumers when compared to the traditional cost by taking the individual consumer preferences for the loads and the ideal time scheduling for the load, which is obtained from the rebuilding trap.

Simulation results demonstrate that the comparison of the cost incurred by the users obtained by the DSM techniques is satisfiable.

There are 29 million homes in the UK, accounting for 14% of the UK's energy consumption. This is given that UK has one of the highest water and energy demands in Europe which needs to be addressed according to the Committee on Climate Change (CCC). Smart homes technology holds a current perception that it is principally used by “tech-savvy” users with larger budgets. However, smart home technology can be used to control water, heat and energy in the entire house. This paper investigates how smart home technology could be effectively utilised to aid the UK government in meeting climate change targets and to mitigate the environmental impact of a home in use towards reducing carbon emissions.

Both primary and secondary data were sought to gain insight into the research problem. An epistemological approach to this research is to use interpretivism to analyse data gathered via a semi-structured survey. Two groups of participants were approached: (1) professionals who are deemed knowledgeable about smart home development and implementation and (2) users of smart home technology. A variety of open-ended questions were formulated, allowing participants to elaborate by exploring issues and providing detailed qualitative responses based on their experience in this area which were interpreted quantitatively for clearer analysis.

With fossil fuel reserves depleting, there is an urgency for renewable, low carbon energy sources to reduce the 5 tonnes annual carbon emissions from a UK household. This requires a multi-faceted and a multimethod approach, relying on the involvement of both the general public and the government in order to be effective. By advancing energy grids to make them more efficient and reliable, concomitant necessitates a drastic change in the way of life and philosophy of homeowners when contemplating a reduction of carbon emissions. If both parties are able to do so, the UK is more likely to reach its 2050 net-zero carbon goal. The presence of a smart meter within the household is equally pivotal. It has a positive effect of reducing the amount of carbon emissions and hence more need to be installed.

Further research is needed using a larger study sample to achieve more accurate and acceptable generalisations about any future course of action. Further investigation on the specifics of smart technology within the UK household is also needed to reduce the energy consumption in order to meet net-zero carbon 2050 targets due to failures of legislation.

For smart homes manufacturers and suppliers, more emphasis should be placed to enhance compatibility and interoperability of appliances and devices using different platform and creating more user's friendly manuals supported by step-by-step visual to support homeowners in the light of the wealth of knowledge base generated over the past few years. For homeowners, more emphasis should be placed on creating online knowledge management platform easily accessible which provide virtual support and technical advice to home owners to deal with any operational and technical issues or IT glitches. Developing technical design online platform for built environment professionals on incorporating smart sensors and environmentally beneficial technology during early design and construction stages towards achieving low to zero carbon homes.

This paper bridges a significant gap in the body of knowledge in term of its scope, theoretical validity and practical applicability, highlighting the impact of using smart home technology on the environment. It provides an insight into how the UK government could utilise smart home technology in order to reduce its carbon emission by identifying the potential link between using smart home technology and environmental sustainability in tackling and mitigating climate change. The findings can be applied to other building types and has the potential to employ aspects of smart home technology in order to manage energy and water usage including but not limited to healthcare, commercial and industrial buildings.

The purpose of this paper is to outline the level of audible carbon monoxide (CO) alarm ownership. In this particular paper the data collected by the fire and rescue services from West Midlands and Merseyside will be analysed, and discussed.

Research was conducted in two stages. Using the indices of multiple deprivation identified whether households in the top and bottom four areas owned an audible alarm. In stage two data loggers were placed into homes to take readings every minute for a total period of three days to three weeks.

There was a noticeable trend that deprived areas were less likely to own audible CO alarms than homes in non-deprived areas. All homes surveyed in stage two had CO levels >0 which further emphasises that anyone can be under health risk and that perhaps the maintenance of gas appliances and other sources is not being conducted at regular intervals.

This paper aims to raise awareness regarding not only the symptoms during CO poisoning but also the ones that have been reported to occur after treatment. It will also disseminate information as to what areas have low alarm ownership and thus more at risk of poisoning. It is hoped that findings from papers such as this one will promote more stringent maintenance and replacement requirements for gas or solid fuel appliances.

Pilot study for the comparison of two English cities has not been conducted before and may lead to more studies of this kind.