Smart Consumer Research Articles

Psychological Aspects of Fashion Brands

The Psychology of Consumers is based on the image of the present Fashion brand has made. There is an emotional connection between consumer & Brand image which influences Consumer’s purchase. Not only this, but the comparison between various brands have also led consumer smart way of understanding which Brand caters what. This paper is a detailed study of Brand comparison about what makes it a niche and different from others. It includes a comparative analysis of brand strategies, positioning, Fashion elements & forte. It employs a mix of quantitative and qualitative research. By exploring key dimensions like Fabric, Style, Color story, pricing, and brand story, this research highlights distinctive attributes that contribute to the success of the brand. The findings enhance the competitive advantage in a dynamic market.

Utilizing Internet of Things (IOT)-based Design for Consumer Loyalty: A Digital System Integration

The purpose of this research is to describe the design of a digital system to create IOT-based customer loyalty. The application of IOT systems for the banking sector is inevitable as part of the widespread positive impact of communication and information technology. The method used in this research is to use literature review by reading a lot of previous research which is the basis for this research by reading a lot of research, the author will be able to better understand the ongoing research by reading a lot of books and journals of previous research, new problems will be found and can be used as future research. The result of this research is a proposed system that can be used as a reference for further research, and can be used as an applied system so that the existing system can be further developed and can be even better, the proposed system produces the latest system using IoT and is expected to produce a smart consumer loyalty system.

Consumer Protection Against Unfair Contract Terms in the Age of Smart Contracts

Smart contracts are designed to be self-executing and self-enforcing. They are written as computer code that can automatically monitor, execute and enforce the performance of the agreed terms. The code of smart contracts exists across a distributed, decentralised blockchain network, controlling the execution and making transactions trackable and irreversible. This article examines the extent to which the Australian Consumer Law unfair contract term provisions can respond to the use of smart contracts. The article finds that the Australian Consumer Law unfair contract term provisions work relatively well to protect smart contract consumers. While some challenges exist and should be properly considered, there seems to be no need to either create entirely new law, modify the existing regime or totally ban smart contracts to protect consumers against unfair contract terms in smart consumer contracts.

The importance of battery storage systems in reducing grid issues in sector-coupled and renewable low-voltage grids

Transforming the energy system towards renewable energies and the electrification of the transport and heating sectors is necessary. A substantial part of this transformation occurs in the low-voltage grids. The increasing number of photovoltaic systems, electric vehicles and heat pumps poses new challenges for low-voltage grids. The load on lines and transformers is increasing due to higher electricity demand. Battery storage systems and the flexible operation of consumers can increase photovoltaic self-consumption and relieve low-voltage grids by using a grid-serving mode of operation and thus supplement grid expansion.We conducted time series-based load flow calculations using five representative low-voltage grids for four weeks of the year. We determined the loads and the need for curtailment caused by a high expansion of roof-mounted photovoltaic systems and new sector-coupled consumers and how these loads and curtailment can be reduced with the help of battery storage systems and flexible consumers.Our analyses show that consumption-related overloads can be completely avoided, and the share of locally consumed photovoltaic energy can be doubled. Digitalising the low-voltage grids is required to detect overloads and allow battery storage systems and consumers to react specifically to these grid overloads. Rural low-voltage grids are particularly affected by overloads, as they have greater rooftop photovoltaic potential and tend to be weaker. Battery storage systems and smart consumers are thus becoming essential cornerstones for the transformation of the energy system.

Adaptive Energy Management of Big Data Analytics in Smart Grids

The smart grid (SG) ensures the flow of electricity and data between suppliers and consumers. The reliability and security of data also play an important role in the overall management. This can be achieved with the help of adaptive energy management (AEM). This research aims to highlight the big data issues and challenges faced by AEM employed in SG networks. In this paper, we will discuss the most commonly used data processing methods and will give a detailed comparison between the outputs of some of these methods. We consider a dataset of 50,000 instances from consumer smart meters and 10,000 attributes from previous fault data and 12 attributes. The comparison will tell us about the reliability, stability, and accuracy of the system by comparing the output of the various graphical plots of these methods. The accuracy percentage of the linear regression method is 98%; for the logistic regression method, it is 96%; and for K-Nearest Neighbors, it is 92%. The results show that the linear regression method applied gives the highest accuracy compared to logistic regression and K-Nearest Neighbors methods for prediction analysis of big data in SGs. This will ensure their use in future research in this field.

MindMiner: Uncovering linguistic markers of mind perception as a new lens to understand consumer–smart object relationships

AbstractPrior research revealed a striking heterogeneity of how consumers view smart objects, from seeing them as helpful partners to merely a useful tool. We draw on mind perception theory to assess whether the attribution of mental states to smart objects reveals differences in consumer–smart object relationships and device usage. We train a language model to unobtrusively predict mind perception in smart objects from consumer‐generated text. We provide a rich set of interpretable linguistic markers for mind perception, drawing on a diverse collection of text‐mining techniques, and demonstrate that greater mind perception is associated with expressing a more communal (vs. instrumental) relationship with the device and using it more expansively. We find converging evidence for these associations using over 20,000 real‐world customer reviews and also provide causal evidence that inducing a more communal (vs. instrumental) relationship with a smart object enhances mind perception and in turn increases the number of tasks consumers engage in with the device. These findings have important implications for the role of mind perception as a novel lens to study consumer–smart object relationships. We offer an easy‐to‐use web interface to access our language model using researchers own data or to fine‐tune the model to entirely new domains.

БАЛАНСИРОВКА ФАЗНЫХ НАГРУЗОК В НИЗКОВОЛЬТНЫХ ТРЕХФАЗНЫХ ЧЕТЫРЕХПРОВОДНЫХ СЕТЯХ

The imbalance of phase loads is a natural negative property of a low-voltage three-phase four-wire network due to uneven connection to the phases and the difference in individual consumer demand for electricity. The imbalance of phase loads in the network nodes leads to a decrease in the quality of electricity, overestimated technical losses in the network and to current overloads in one of the phases of power lines. In the paper, balancing of phase loads in the network is performed using a heuristic algorithm based on average hourly readings of loads and voltages readings of consumer smart meters. The effectiveness of the algorithm was evaluated by reducing losses, maximum currents in the phase wires and the neutral wire in a real feeder of the electrical network

Performance Evaluation of Communication Infrastructure for Peer-to-Peer Energy Trading in Community Microgrids

With the rapidly growing energy consumption and the rising number of prosumers, next-generation energy management systems are facing significant impacts by peer-to-peer (P2P) energy trading, which will enable prosumers to sell and purchase energy locally. Until now, the large-scale deployment of P2P energy trading has still posed many technical challenges for both physical and virtual layers. Although the communication infrastructure represents the cornerstone to enabling real-time monitoring and control, less attention has been given to the performance of different communication technologies to support P2P implementations. This work investigates the scalability and performance of the communication infrastructure that supports P2P energy trading on a community microgrid. Five levels make up the developed P2P architecture: the power grid, communication network, cloud management, blockchain, and application. Based on the IEC 61850 standard, we developed a communication network model for a smart consumer that comprised renewable energy sources and energy storage devices. Two different scenarios were investigated: a home area network for a smart prosumer and a neighborhood area network for a community-based P2P architecture. Through simulations, the suggested network models were assessed for their channel bandwidth and end-to-end latency utilizing different communication technologies.

ICT as a Support for Value Chain Management in Tourism Destinations: The Case of the City of Cuenca, Ecuador

The accelerated development of information and communication technologies (ICTs) has had an impact on the way tourism is carried out today. The concept of smart cities and smart destinations is gaining momentum, which also requires smart consumers, i.e., informed, communicated, and connected. In this sense, the application of the value chain concept to tourism implies reconsidering the weight of digital technologies in its structure and, therefore, in the decision-making process of current and potential tourists. The study aims to demonstrate the need and convenience of incorporating technology as an innovative factor in the management process of the tourism value chain and its contribution to the positioning of the destination, taking the city of Cuenca (Ecuador) as a case study. The contributions are, firstly, the ICT adoption as an innovation factor in the value chain. In addition, through a survey of foreign tourists, it was verified that ICTs are a trend as a personalized communication channel, which contributes to valuing the integral tourism offer of the territory.

Higher education-based teacher educators’ researcherly disposition: An international perspective

ABSTRACT By presenting the results of a large-scale international study, this study targets a better empirical understanding of teacher educators’ researcherly disposition or the teacher educators' habit of mind to engage with research to improve their practice and contribute to the knowledge base on teacher education. Data was collected from an international sample of 1158 higher education-based teacher educators in six countries, most of them being European. The first part of the article reports on the development of iTERDS, i.e. the international Teacher Educators’ Researcherly Disposition Scale. This 16-item scale distinguishes three subdimensions: (1) Valuing research (6 items), (2) Being a smart consumer of research (5 items), and (3) Being a producer of research (5 items). Goodness of fit estimates indicate good fit. The second part of the article explores differences in teacher educators’ researcherly disposition by means of cluster analysis. Four different clusters of teacher educators were found: Cluster 1 ‘inactive to research teacher educators’, Cluster 2 ‘well-read teacher educators’, Cluster 3 ‘researching teacher educators’, and Cluster 4 ‘teacher educator-researchers’. Post hoc analyses on these clusters explore relevant background differences between the clusters in terms of qualifications and work context.

Evaluating Consumer Behavior, Decision Making, Risks, and Challenges for Buying an IoT Product

Home appliance manufacturers have been adding Wi-Fi modules and sensors to devices to make them ‘smart’ since the early 2010s. However, consumers are still largely unaware of what kind of sensors are used in these devices. In fact, they usually do not even realize that smart devices require an interaction of hardware and software since the smart device software is not immediately apparent. In this paper, we explore how providing additional information on these misunderstood smart device features (such as lists of sensors, software updates, and warranties) can influence consumers’ purchase decisions. We analyze how additional information on software update warranty (SUW) and the type of sensors in smart devices (which draw attention to potential financial and privacy risks) mediates consumer purchase behavior. We also examine how other moderators, such as brand trust and product price, affect consumers’ purchase decisions when considering which smart product option to buy. In the first qualitative user study, we conducted interviews with 20 study participants, and the results show that providing additional information about software updates and lists of sensors had a significant impact on consumer purchase preference. In our second quantitative study, we surveyed 323 participants to determine consumers’ willingness to pay for a SUW. From this, we saw that users were more willing to pay for Lifetime SUW on a smart TV than to pay for a 5-year SUW. These results provide important information to smart device manufacturers and designers on elements that improve trust in their brand, thus increasing the likelihood that consumers will purchase their smart devices. Furthermore, addressing the general consumer smart device knowledge gap by providing this relevant information could lead to a significant increase in consumer adoption of smart products overall, which would benefit the industry as a whole.

A four-stage stochastic framework for managing electricity market by participating smart buildings and electric vehicles: Towards smart cities with active end-users

After the restructuring of the electricity market, one of the challenges of researchers has always been to design markets that can use the maximum potential of smart consumers to improve the economic and technical indicators of the system. Therefore, this article presents a four-stage model in which the scheduling of smart buildings, microgrids and the main grid is done. In the first stage of this model, subscribers of smart buildings do their day-ahead scheduling with the aim of minimizing their electricity bill and send it to the central control unit of the building. In the second stage, the central control unit of the smart building performs its day-ahead scheduling according to the received programs and sends it to the microgrid operator. Then, in the third stage, the microgrid's strategy for participating in the day-ahead market is designed, considering the programs received from smart buildings. Finally, in the fourth stage, the market manager receives buy / sell offers of microgrids and calculates the market settlement price (MSP) with the aim of maximizing the social welfare (SW) index. The simulation results illustrate that equipping smart buildings with solar panels and energy storage systems (ESSs) not only reduces the MSP during peak hour by 6.66%, but also improves the network voltage profile. In addition, the results reflect that changing the behavior of smart subscribers and electric vehicles (EVs) by the incentive programs leads to a significant improvement of the technical and economic indicators of the network.

Effective environmental education for sustainable development beyond the Plastic Age in South Korea

The skyrocketing single-plastic demand during the coronavirus disease 2019 (COVID-19) pandemic proved the limitation of top-down environmental policies in accomplishing sustainable consumption and waste management. Nevertheless, ‘smart consumers’ can make smart choices for sustainable development. However, a review of the South Korean environmental education curriculum reveals that the current structure heavily leans towards the elementary level and does not enlighten the public on ‘what’ and ‘how’ to live sustainably. This study uses a quick survey to suggest that the effectiveness of environmental education may be enhanced if: (1) guidance on how to live with the natural environment in harmony for collective cooperation towards resilient and sustainable community building is incorporated with a clear purpose, (2) environment-friendly culture-building activities are enforced to institutionalise a new paradigm of sustainability to replace today’s consumerism, and (3) contents are updated regularly to include Earth and environmental science knowledge in the state of art.

Digital care at home: Exploring the role of smart consumer devices.

In-home 'smart' consumer devices such as voice assistants, doorbells, thermostats, and lightbulbs have been advocated by organisations in the UK such as the RNIB, Alzheimer Scotland, and the NHS. Yet the use of these devices, which are not purposely designed as care devices and therefore are not subject to evaluation and regulation, has been neglected in the academic literature. This paper reports on a study which examined 135 Amazon reviews of 5 'top-selling' smart devices, concluding that such devices are being used to supplement informal caring, albeit in different ways. The implications of this phenomena are necessary to consider, specifically the consequences for 'caring webs' and expectations about the future role of digital devices within the landscape of informal caring.

INFLUENCE OF PRODUCT QUALITY, PRICE PERCEPTION, AND QUALITY OF SERVICE, ON SMARTFREN REPURCHASING INTEREST IN THE COVID-19 PANDEMIC (Survey of Smartfren Internet Service Users in the Special Region of Yogyakarta)

This study aims to determine the effect of product quality, price perception, and service quality on repurchase interest This research method uses quantitative methods with a survey approach. The sample in this study amounted to 120 respondents. The sampling technique in this study used a non-probability sampling technique with purpose sampling with the criteria of respondents being smart consumers who live in the Special Region of Yogyakarta and have made purchases three times during the covid-19 pandemic. The results of this study indicate that product quality, price perception, and service quality together have a positive and significant impact on the intention to repurchase Smartfren internet services in the Special Region of Yogyakarta during the covid-19 pandemic. Keywords: Product Quality, Price Perception, Service Quality, Repurchase Interest,

Top 12 layer-wise security challenges and a secure architectural solution for Internet of Things

Digitalization, intelligent virtual assistants, and smart consumer products prepare us for life at every stage. Smart IoT, Sensor nodes, software communicate with one another via voice and emotions, simplifying our lives. Smart IoT is becoming more prevalent in our daily lives. Even though the use of Smart IOTs has grown in Geometric progression, the security of these devices remains traditional. Technically, most security discussions revolve around the implementation of better Network Intrusion Prevention/Detection Systems (NIPS/NIDS), the installation of a traditional firewall, or the use of proxy scanners, which is the standard recommendation of security vendors. All architectures are rooted in the same zeal that drives cyber warfare. However, when considering the Narrowband Internet of Things, the packet size is too small, and the memory and processors are so small that they cannot hold the packets for inspections, and the lucrative protocols will not work. Malicious hackers, BOTs, Trozens, and Honeypots may tamper with and virtually control these smart Internet of Things (IoT) to steal/tamper sensitive information for filthy lucre, financial reward, or, to put it simply, money in this cyber warfare. All of these issues stem from a lack of proper security design controls, architectural security flaws, and a failure to apply Secure by Design principles. Fixing these security controls earlier in the process will save us a significant amount of time, energy, and money spent on repairing broken IoT security flaws and performance aesthetics. If we consider the Shift Left Secure by Design/Architecture Journey in the Internet of Things Security Architecture, these Architectural/Design flaws can be identified in earlier stages and will help the delivery teams to plan necessary security controls in the IoT use cases.In this paper, the author discusses Layer-wise Security Challenges, Attack Vectors, and Architectural Flaws, and proposes a secure architectural solution for the Internet of Things (IoT) that assists delivery teams in securely designing/architecting resource-intensive smart Internet of Things (IoT)/Narrowband (NIoT) use cases earlier in the Life cycle by employing the Secure Design Shift Left approach. In this smart digital IoT era, the author also suggests future research directions for future generations to increase security.

Smart Consumer Wearables as Digital Diagnostic Tools: A Review.

The increasing usage of smart wearable devices has made an impact not only on the lifestyle of the users, but also on biological research and personalized healthcare services. These devices, which carry different types of sensors, have emerged as personalized digital diagnostic tools. Data from such devices have enabled the prediction and detection of various physiological as well as psychological conditions and diseases. In this review, we have focused on the diagnostic applications of wrist-worn wearables to detect multiple diseases such as cardiovascular diseases, neurological disorders, fatty liver diseases, and metabolic disorders, including diabetes, sleep quality, and psychological illnesses. The fruitful usage of wearables requires fast and insightful data analysis, which is feasible through machine learning. In this review, we have also discussed various machine-learning applications and outcomes for wearable data analyses. Finally, we have discussed the current challenges with wearable usage and data, and the future perspectives of wearable devices as diagnostic tools for research and personalized healthcare domains.

A Simple, Low-cost, Efficient and Smart Consumer Gas Leakage Detection System

Liquefied Petroleum Gas is used for a wide range of both domestic and industrial purposes. Its use has seen a significant increase over the years. Unfortunately, there have also been many casualties resulting from gas explosions in recent times. Often, there is a news report of a gas explosion occurring somewhere, whether at home, in the marketplace or in an industry. Although these accidental explosions are sometimes beyond human control, some are due to ignorance, negligence, or improper care of gas cylinders. Most explosions are caused by undetected gas leakages which are then set off to explode with the slightest ignition. Apart from explosions, fires at homes can also be caused by gas leakages. This usually results in serious injuries, loss of property and even sometimes, loss of lives. This project seeks to provide a smart, budget friendly and easy to use gas leakage detector system, a better alternative to relying on the natural way of using the nose, which may fail and in effect, incur undesirable consequences. The system employs an MQ2 sensor interfaced with an ESP8266 Wi-Fi module for sensing the gas in the atmosphere and displaying an alert message on the lcd. The Wi-Fi in combination with the microcontroller module acts as the transmission and processing unit, allowing for communication over wireless medium. This way, a user can receive notifications on a mobile device depending on changes the hardware system detects in the atmosphere. There is also a buzzer to alert nearby persons by sound so that they can take the necessary precautions and actions

THE ROLE OF COURSES IN INFLUENCING SMART CONSUMER BEHAVIOUR OF SENIOR HIGH SCHOOL STUDENTS IN RURAL AND URBAN AREAS

Consumer education interventions through formal education can increase knowledge, attitudes, and behaviour to become smart consumers who can enforce their rights, carry out their obligations, and protect themselves from harmful goods or services. This study aims to analyze differences in awareness of consumer education materials, sources of information, attitudes, and behaviour as savvy consumers in high school students in rural and urban Bogor and the factors that influence smart consumer behaviour. This study used a cross-sectional study design and involved two senior high schools located in the rural and urban areas of Bogor. The location selection was performed purposively, considering that the school implemented the Education Unit Level Curriculum (KTSP) and used the Electronic School Book (BSE). The sampling technique used random cluster sampling with a sample size of 129 high school students, 68 students in rural areas and 61 students in urban areas. The results showed significant differences in the material awareness of consumer rights variables and the three attitude dimensions. On the contrary, there was no difference in material awareness of consumer obligations, objective knowledge of rights and obligations and significant smart consumer behaviour on smart consumer behaviour in both regions. Students' age, objective knowledge about consumer obligations, and attitudes (affective and conative dimensions) significantly positively affect smart consumer behaviour in high school students.

Are Prior Smart Hotel Visiting Experience and Personal Innovativeness Critical to Future Visit Intention?

ABSTRACT This study explores the relationship between consumer perception of smart hotel technology amenities (TA) and consumer visit intention to smart hotels. The mediating role in this relationship is examined by technology acceptance model (TAM). The study also examines whether prior smart hotel visiting experience and personal innovativeness can moderate this relationship. An online survey was carried out with 617 Chinese consumers. Empirical results of structural equation modeling and PROCESS show that prior visiting experience has a moderating effect but PI is not shown to have any moderating effect. This study offers further implications to capitalize on consumer loyalty.