Consumer Information Research Articles

How to Avoid the Harm of Big Data Technology to Consumers Rights Through Law

Merchants collect and use consumers confidence collected actively or passively. When platform operators go beyond a specific range, collect and use consumer information unrestrainedly, use algorithm technology to precisely portray consumers, implement differentiated pricing, and conduct considerable data-enabled price discrimination. On the one hand, the behavior of killing familiarity with big data violates the legitimate rights and interests of consumers, wears away consumers loyalty to the Internet industry, and hinders the conclusion of commercial transactions by inaction; on the other hand, the retail credit of platform operators is also virtually reduced. Over time, it is straightforward for consumers to have a crisis of trust in platform operators, affecting the conclusion of commercial transactions. This article starts with three judicial cases and analyzes the illegality of big data killing the rights of consumers from the perspective of theory and practice and what causes big data killing. To better protect the rights and interests of consumers, it also explores How to avoid the behavior of killing familiarity with big data through legal means.

Benefit evaluation analysis of new energy power consumption information collection with basic steady-state harmonic characteristics

Abstract In this paper, firstly, the load monitoring characteristics of new energy power consumption are studied and analyzed in terms of both steady-state and transient characteristics, and suitable characteristic values are selected for different types as the basis of load decomposition. A comparative analysis of various types of load imprints is conducted to highlight the advantages of steady-state harmonic features as load monitoring feature data. Then, an evaluation model of the demand response potential of electricity information collection is established based on a multi-objective optimization algorithm, and technical and economic analysis of electricity information collection is carried out to evaluate the response potential of power companies collecting customer data. Finally, the situation and benefits of collecting electricity consumption information for new energy power are analyzed. The daily maximum load moments of typical users are all cut by more than 10%, the peak load portion cut by more than 97% is also more obvious, and the maximum moments of valley filling response are all more than 11%. D Power saved a total of 3.759 billion yuan in labor costs by reducing labor costs by 400 million yuan after adopting electricity consumption information collection. The indices of excellent and qualified management benefit and social benefit evaluation of electricity consumption information collection are above 0.8. Overall, the benefits of electricity consumption information collection for new energy power with basic steady-state harmonic characteristics are significant and effective.

Research on the development of AloT sensing module for new energy power information collection

Abstract In order to improve the ability of power communication technology to support large-scale and massive services of smart electricity consumption, this paper designs a sensing model to collect information on new energy electricity consumption. Using the arrival rate calculation method of intelligent IoT, the information on new energy electricity users is collected, and the environmental measurement data is collected with the help of intelligent sensors. Monitoring the concurrency factor of all sensors in the operation state, collecting queuing theory packet loss rate through utilization maximization objective function, and setting the average queuing length of communication nodes. On this basis, the voltage amplitude of the electrical energy sampling point is measured, and the Gaussian perceptual loss vector with non-zero mean and heteroskedasticity is performed to iteratively converge the constraint matrix and error covariance. The results show that the maximum relative errors for service delay and packet loss rate are 16.8% and 7.0%, respectively. As bandwidth increases, the queuing delay and packet loss rate decrease. The broadband power line carrier can reach up to 210 Mbps, and the micropower wireless rate can reach 38.5 kbps. The annual cycle characteristics fluctuate widely, but the cumulative error of electricity load prediction results is lower, and the prediction accuracy is high. It shows that the electricity consumption information collection sensing model provides an important reference for building a new communication network with low cost, high speed and reliability for smart electricity consumption.

RSSI-adaptive local dual-mode communication for the Internet of Things in power distribution

Abstract The Internet of Things (IoT)’s rapid development is placing new demands on communication technology for power distribution. This paper proposes the application scheme of RSSI adaptive and dual-mode communication technology in the power distribution area, realizes the dual-mode networking technology adopted to improve communication quality, and verifies the reliability and superiority of the dual-mode communication technology scheme through analysis and application. The RSSI adaptive dual-mode communication module is designed, the RSSI model algorithm is modified, and the logical topology of the communication network and the data processing technology based on compressed sensing are analyzed. We focus on analyzing the performance of dual-mode communication networks for power consumption information collection and the information reception rate and real-time performance of MQTT protocol mapping for power distribution IoT. The average transmission delay was tested to be 198.5ms for QoS=0, 478.0ms for QoS=1, and 786.3ms for QoS=2 without encryption. When using SASL/TLS for transmission encryption, the average transmission delay is 992.7ms for QoS=0, 1203.6ms for QoS=1, and 1461.1ms for QoS=2.

THE IMPACT OF ONLINE REVIEWS ON CONSUMER DECISION-MAKING: A SURVEY IN THE UKRAINIAN MARKET

Online reviews are a powerful source of information for consumers, especially in emerging markets such as Ukraine. However, little is known about how online reviews affect consumer behavior in this context. This paper aims to fill this gap by conducting a survey of 321 Ukrainian consumers who have used online reviews for their purchase decisions. The paper explores the impact of online reviews on consumer decision-making, the motivations and barriers for writing and reading reviews, the elements of convincing and suspicious reviews, and the trustworthiness of online reviews compared to other sources of information. The paper also examines the cultural and social factors that shape consumer preferences and expectations, such as the war situation, ethical behavior, and CSR initiatives. The paper provides valuable insights for businesses that want to leverage online reviews to enhance their online presence and customer relationships in the Ukrainian market. The paper also contributes to the literature on consumer behavior and online reviews, and suggests directions for future research.

Ethical and safety considerations in automated fake news detection

ABSTRACT This paper highlights ethical issues in automated fake news detection and calls for caution when deploying tools to automatically detect mis/disinformation in real-life settings. We argue that the potential harm to information consumers caused by an automated tool making a mistake requires us to better understand the mistakes that can be made. We implement three proposed detection models from the literature that were trained on over 381,000 news articles published over six months. We test each of these models using a test dataset constructed from over 140,000 news articles published a month after each model’s training data. Articles in the test dataset could come from any outlet, no matter if that outlet was labelled during training or never used during training. We used these data to explore and understand two specific problems with algorithmic fake news detection, namely Bias and Generalisability. These problems arise from the models’ training, design, and the inherent unpredictability of news content. Based on our analysis, we discuss the importance of understanding how ground truth is determined, how operationalisation may perpetuate bias, and how the simplification of models may impact the validity of predictions. We offer avenues for future research.

PECULIARITIES AND TASKS OF CIVIC EDUCATION IN UKRAINE IN THE CONTEXT OF ARMED AND INFORMATIONAL AGGRESSION

The article examines the role and significance of civic education in the context of socio-cultural development of society and strengthening the international status of the state. The main attention is paid to the historical aspect of civic education, its impact on the formation of a citizen in accordance with the standards of the democratic European state system. The article highlights different interpretations of civic education at different stages of history, from ancient times to modern times. A separate section is dedicated to the analysis of civic education in the modern socio-humanitarian discourse, in particular its place in the fields of philosophy, pedagogy and political science. The final part emphasizes the challenges that civic education poses to various sectors of society in the modern world.The article also emphasizes the importance of civic education as a tool for transferring values and cultural heritage from one generation to another, the role of education in strengthening the authority of the state at the international level and its influence on the formation of a conscious citizen in the conditions of changing geopolitical realities. Through the prism of the analysis of different historical contexts, it is investigated how civic education reflects the ideals, standards and values of different eras, its role in social integration and strengthening of national identity.Looking at education through the prism of philosophy, we can see it not only as a process of imparting knowledge, but also as a dialogic practice, where each participant is not just a consumer of information, but also an active participant in the process of learning. Also, in the context of modern globalization, it is important to pay attention to the intercultural dimension of education. How can we ensure that the educational process promotes mutual understanding between different cultures, instead of separating and dividing them? The answer to these questions requires not only philosophical reflection, but also pedagogical innovation. The philosophy of education should serve as a bridge between theory and practice, prompting rethinking and improvement of the educational process at all its levels.The final part of the article emphasizes the urgency of reforming the system of civic education in modern conditions, taking into account globalization processes and the growing need to train educated, critically thinking citizens who are able to adapt to the rapidly changing conditions of the modern world. This need is especially felt in the context of armed and informational challenges that Ukraine has faced in recent years.Keywords: civic education, values, cultural heritage, philosophy of education, historical context.

Examining Public Perceptions of Algorithm Transparency: An Empirical Analysis

In the rapidly evolving landscape of the digital age, algorithms have become pivotal components of various systems, influencing the information and content consumers encounter. This empirical analysis delves into algorithm transparencys intricate relationship and implications for consumer perception, trust, and behavioral intention. Given the prevalence of algorithms in shaping the digital media and consumption landscape, comprehending the publics opinions and comprehension of algorithm transparency has gained paramount significance. Preliminary findings from this research spotlight the pivotal role of algorithm transparency in molding consumer trust and decision-making processes. As consumers increasingly interact with algorithmically curated content and recommendations, the transparency surrounding these algorithms substantially influences how individuals perceive and interact with such technologies. The studys outcomes offer valuable insights for policymakers, businesses, and developers aiming to enhance user experiences, strengthen consumer trust, and fine-tune algorithms that align with public expectations. In conclusion, this empirical analysis represents a critical step toward unraveling the multifaceted relationship between algorithm transparency and its impact on consumer behavior. In a digital landscape characterized by ubiquitous algorithms, understanding how transparency shapes perceptions and decisions is academically intriguing and practically imperative for fostering healthier digital interactions.

Price and variety in the Salop model

AbstractUsing a Salop circle model, this research analyzes the welfare implications of firm/product entry with information provision by consumers. While firms use consumer information to target sales efforts, consumers face privacy trade‐offs when providing their personal information. We show that (i) price and profit first increase, then decrease with more varieties; (ii) consumer welfare, affected by price, sales effort, privacy loss, and matching effects, first decreases, then increases with firm entry; (iii) equilibrium information is socially optimal given the number of varieties; and (iv) if the variable cost of providing sales assistance is low (high), free entry leads to too much (few) varieties and too little (more) information, from a social welfare standpoint.

Addressing Information Consumer Experience through a User-Centered Information Management System in a Chilean University

Prior research on the successful design and construction of data visualization systems or information management systems has not fully taken into account the holistic experience of employees working with information within the organization but has centered on specific aspects, such as user experience or data quality, attempting to go against information management quality, as those approaches can significantly influence users’ perceptions and their motivation to effectively use such tools for decision making. This study addresses the information consumer experience (ICX) in a Chilean Higher Education institution through the design and implementation of an user-centric centralized information management system. This system was created using an adapted design thinking methodology with an ICX perspective to identify and integrate the information consumers’ demands and other factors correlated with ICX into the system’s design. The proposed system is a technological extension of an information resource validation process that involves senior data analysts from the Analytics Department and external data analysts from other departments across the organization. This process helps to address data quality and information management quality (IMQ) problems of the organization, representing a centralized data source for all information consumers into the organization, offering consistent, accessible, and good quality data to address daily work and enhance information consumers experience, and managerial work.

DESIGN OF ELECTRICAL POWER TELEMETERING SYSTEM USING MICROCONTROLLER DEVICE VIA GSM

Traditionally, reading of energy meters is done by human operators who move from house to house collecting readings. This exercise requires huge labor operator numbers and a lot of time to achieve complete reading of meters in a particular area. This paper endeavors to do away with this problem by using a telemetering system. With this system, power can be measured from a remote site. To achieve this, readings from an energy meter on site are processed by a microcontroller device that then sends the energy consumption information to a Global System Mobile(GSM) module. The GSM module then sends this information using microwaves to a particular mobile subscriber who receives it in the form of an Short Message Service(SMS). The reading is also transmitted to a web based telemetering system through a server. In the remote site, a remote computer which can access the internet is able to obtain data from the server through the internet. The microcontroller is developed in such a way that it achieves communication between the energy meter and the particular server using Transmission Control Protocol(TCP) protocol. Software programs are also developed to facilitate transfer of data to the user at remote site. With the web based telemetering system connected to the internet, electrical energy measurements can be accessed globally. The efficiency of the transmission channel is important for the success of both SMS and web based telemetering systems.

GUARDIANS OF THE COMMUNICATION PROCESS, THEIR FUNCTIONS IN THE FORMATION OF THE MEDIA LANDSCAPE

The proposed study examines the complex and multifaceted communication process, as well as the role of the media in shaping public perception, values, and beliefs. Recognizing the power and responsibility of the mass media for percepting the environment, emphasizing the importance of media literacy and critical thinking of information consumers, we propose to comprehend the key functional of specialists who dramatically influence the media landscape development, agenda molding, as well as “information bubbles” creating that can be as favorable for the further development of the society, as inhibiting it. In our opinion guidekeepers, spin-doctors and news-ombudsmen play the key roles among communication specialists. They influence not only the control and filters of the content broadcast, but also the formation of moral principles of media workers in general and the creation of professional ethical codes. Considering, that modern media platforms serve as the means of spreading social, political, cultural ideas, as well as public discourse of various orientations, it is worth actualizing functions of the media (both individual representatives and platforms in general) such as: conscious design and dissemination of information; management of public perception in order to prevent political and economic crises; ensuring honesty, accountability and transparency between the public and representatives of the media community. Particularly these functions the mentioned media persons are able to provide, as despite the different contextual bases, they all play an important role in the process, management and development of ethical principles of communication.

Breaking the vertical barrier: effects of vertical direction and rotation of an English loan brand name on product evaluation

PurposeThis study investigates the effects of vertical direction and rotation of English loan brand names in East Asian languages (Chinese and Korean) on processing fluency, perceived product quality and purchase intention.Design/methodology/approachFour experiments were conducted in China and Korea, employing a 2 (vertical direction: downward vs upward) X 3 (rotation: 0°/marquee vs 90° clockwise vs 90° counterclockwise) between-subjects factorial design.FindingsThe findings showed that when the English loan Chinese brand name was displayed downward, the marquee format was preferred, while counterclockwise rotation was favored when displayed upward. In Korean, clockwise rotation was preferred for downward presentation, while counterclockwise rotation was favored for upward presentation. The effects on purchase intention were mediated by processing fluency and perceived product quality.Practical implicationsThis research provides practical implications for global manufacturers and retailers, offering guidance on presenting brand names in East Asian languages and optimizing product packaging designs. For Chinese consumers, the marquee format is recommended for downward-oriented brand names, while counterclockwise rotation is effective for upward orientation. For Korean consumers, clockwise rotation is favored for downward presentation and counterclockwise rotation is preferred for upward presentation. Understanding linguistic habits allows the tailoring of brand presentations, enhancing brand perception and consumer responses.Originality/valueThis study contributes to understanding the role of cultural and linguistic influences on consumer information processing and product perception in vertical presentations of brand names.

Sentiment Analysis of Chinese Product Reviews Based on Fusion of DUAL-Channel BiLSTM and Self-Attention

Product reviews provide crucial information for both consumers and businesses, offering insights needed before purchasing a product or service. However, existing sentiment analysis methods, especially for Chinese language, struggle to effectively capture contextual information due to the complex semantics, multiple sentiment polarities, and long-term dependencies between words. In this paper, we propose a sentiment classification method based on the BiLSTM algorithm to address these challenges in natural language processing. Self-Attention-CNN BiLSTM (SAC-BiLSTM) leverages dual channels to extract features from both character-level embeddings and word-level embeddings. It combines BiLSTM and Self-Attention mechanisms for feature extraction and weight allocation, aiming to overcome the limitations in mining contextual information. Experiments were conducted on the onlineshopping10cats dataset, which is a standard corpus of e-commerce shopping reviews available in the ChineseNlpCorpus 2018. The experimental results demonstrate the effectiveness of our proposed algorithm, with Recall, Precision, and F1 scores reaching 0.9409, 0.9369, and 0.9404, respectively.

Unexpected obstacles in mechanical recycling of polypropylene labels: Are ambitious recycling targets achievable?

Recycling initiatives like the ‘Green Deal’, aspire to achieve complete recyclability for packaging materials and previously overlooked recycling fractions, but they might face practical challenges. We investigated the mechanical, processing, and toxicological properties of polypropylene labels during mechanical recycling to gain insight into dealing with as yet unutilized recycling fractions. Possible challenges during recycling include label pigments shifting infrared spectra bands and promoting β-spherulite nucleation, which can cause homopolymer melting peaks to resemble copolymers or multilayered structures. Label blends also do not conform to the straightforward rules of linear mixing. This means that predicting mold and machine parameters for blends of virgin and recycled material becomes challenging. The elongation at break of these blends is also influenced by the presence of labels, with noticeable deterioration effects even at label concentrations as low as 20 wt.%. Moreover, labels contain substances classified as Cramer Class III, with DNA-reactive mutagenicity responses present in processed and unprocessed labels. Despite labels ultimately being recyclable and potentially repurposable for extrusion or injection molding applications, their complex processing requirements, safety concerns, and limited economic viability may make them more valuable indirectly, on a systemic level, providing useful information for consumers including on the disposal and recyclability of packaging.

Analysing Health Insurance Customer Dataset to Determine Cross-Selling Potential

Health insurance cross-selling refers to the practice of offering additional or complementary insurance products to existing policyholders. Insurance providers leverage cross-selling, offering customers additional policies like dental or life insurance when they already have a basic health insurance plan. This study is conducted to focus on the application of machine learning techniques to predict health insurance cross-selling opportunities among South African customers. The aim of this study is to develop a cross-selling predictive machine learning model that can assist health insurance companies to identify potential customers for cross-selling probabilities. To achieve this goal, a quantitative research methodology is adopted, focusing on extracting a comprehensive dataset of health insurance consumer information and employing various machine learning algorithms using the Python programming language, including Random Forest, K-Nearest Neighbours, XGBoost classifier, and Logistic Regression algorithms to build the cross-selling predictive machine learning model. The experimental results obtained demonstrate the accuracy scores of four different machine learning algorithms trained using 1,000,000 customer dataset with 17 features, logistic regression is considered as the top-performing model. It achieved an accuracy score of 0.83 and an F1 score of 0.91. The analysis indicates that customers aged 30-60, with prior insurance, and longer service history are more likely to buy additional health insurance products. The findings of this research can help health insurers boost revenue by improving their customer targeting and retention strategies.

An Empirical Study on the Effects of Information Characteristics in Influencer Marketing on Consumers’ Purchase Intention

With the continuous development of digital business, influencer marketing has gradually become a regular marketing strategy. In this marketing context, on the one hand, influencers play an indispensable role in recommending products and delivering information to consumers, and on the other hand, the proportion of the information released by influencers on consumers' purchasing intention has gradually increased, and more consumers are willing to trust the information recommended by influencers and thus generate corresponding consumption behaviours. Therefore, how information from influencers can contribute to the development of influencer marketing has become a focus of attention in both academia and industry. This study confirms the positive effect of consumers’ perceived information characteristics on purchase intention in influencer marketing through empirical experiments and reveals the mediating role of information credibility in it. Furthermore, the relationship between information credibility and consumers’ purchase intention was moderated by parasocial relationship. These findings point to the importance of information characteristics in influencer marketing with a view to providing some references for the enhancement of consumers’ purchase intention in influencer marketing.

Supply chain carbon transparency to consumers via blockchain: does the truth hurt?

PurposeThe purpose of this study is to determine if blockchain-supported carbon offset information provision and shipping options with different cost and environmental footprint implications impact consumer perceptions toward retailers and logistics service providers. Blockchain and carbon neutrality, each can be expensive to adopt and complex to manage, thus getting the “truth” on decarbonization may require additional costs for consumers.Design/methodology/approachExperimental modeling is used to address these critical and emergent issues that influence practices across a set of supply chain actors. Three hypotheses relating to the relationship between blockchain-supported carbon offset information and consumer perceptions and intentions associated with the product and supply chain actors are investigated.FindingsThe results show that consumer confidence increases when supply chain carbon offset information has greater reliability, transparency and traceability as supported by blockchain technology. The authors also find that consumers who are provided visibility into various shipping options and the product's journey carbon emissions and offset – from a blockchain-supported system – they are more willing to pay a premium for both the product and shipping options. Blockchain-supported decarbonization information disclosure in the supply chain can lead to organizational legitimacy and financial gains in return.Originality/valueUnderstanding consumer action and sustainable consumption is critical for organizations seeking carbon neutrality. Currently, the literature on this understanding from a consumer information provision is not well understood, especially with respect to blockchain-supported information transparency, visibility and reliability. Much of the blockchain literature focuses on the upstream. This study focuses more on consumer-level and downstream supply chain blockchain implications for organizations. The study provides a practical roadmap for considering levels of blockchain information activity and consumer interaction.

Does diversity facilitate consumer decisions: a comparative perspective based on single-category versus multi-category products

PurposeThis study aims to explore the opposite effects of single-category versus multi-category products information diversity on consumer decision making. Further, the authors investigate the moderating role of three categories of visitors – direct, hesitant and hedonic – in the relationship between product information diversity and consumer decision making.Design/methodology/approachThe research utilizes a sample of 1,101,062 product click streams from 4,200 consumers. Visitors are clustered using the k-means algorithm. The diversity of information recommendations for single and multi-category products is characterized using granularity and dispersion, respectively. Empirical analysis is conducted to examine their influence on the two-stage decision-making process of heterogeneous online visitors.FindingsThe study reveals that the impact of recommended information diversity on consumer decision making differs significantly between single-category and multiple-category products. Specifically, information diversity in single-category products enhances consumers' click and purchase intention, while information diversity in multiple-category products reduces consumers' click and purchase intention. Moreover, based on the analysis of online visiting heterogeneity, hesitant, direct and hedonic features enhance the positive impact of granularity on consumer decision making; while direct features exacerbate the negative impact of dispersion on consumer decision making.Originality/valueFirst, the article provides support for studies related to information cocoon. Second, the research contributes evidence to support the information overload theory. Third, the research enriches the field of precision marketing theory.

A Novel Consumer Preference Model Based on Blockchain and Topic Similarity Clustering in Cross-Border E-Commerce

Nowadays, countries in the world have frequent economic exchanges, and the scale of cross-border E-Commerce (CBEC) is getting larger and larger. CBEC refers to trading, payment, logistics, customs clearance, and other transactions. It also refers to the services between countries or regions through Internet technology and e-commerce platforms. In this article, the authors proposed a consumer preference model by blockchain and topic similarity clustering to obtain more consumer preference information. First, this article builds a blockchain-based consumer information collection system for CBEC to extract various features of consumers in CBEC. Secondly, by improving the performance of multiple characteristics of consumers, the accuracy of consumer preference prediction is improved. Finally, a method of consumer preference prediction based on topic similarity clustering is proposed to obtain consumers' purchase preference types. Experimental results show that the method can reach 84.3% of the H-mean, getting the best predictive performance and assisting CBEC by predicting consumer preferences.