Product Quality Research Articles

Clinical applications of Sunscreens and formulation advancements.

Sunscreens cover the big market ratio in terms of cosmetic applications, but the therapeutic necessity of sunscreen still needs to be uncovered in the clinical context. Clinically, sunscreens are being employed more often nowadays as a result of the rising consequences of skin malignancies and the photodamaging effects of UV radiation. Sunscreens are essential to prevent aging by shielding the skin from the harmful effects of ultraviolet (UV) radiation. Over the recent decades, there has been a significant evolution in the usage of sunscreens as photo protectants. The demand for sunscreen formulations will inevitably rise as more people become aware of the protection that sunscreens provide against tanning, photoaging, non-melanoma skin cancers, pre-malignant skin lesions, and skin melanomas. The novel contemporary formulation techniques are also beneficial in enhancing the product's aesthetic look and quality. Recently, regulatory agencies have also started paying attention to the regulation of the clinical application, efficacy, and safety parameters related to sunscreen. This review underlines the pathophysiological response of UV exposure with the therapeutic applications of sunscreen in various dermatological conditions and the recent formulation advancements in the development of sunscreen.

Integration of statistical methods and neural networks for temperature regulation parameter optimization

Temperature control plays a crucial role in various industrial processes, ensuring optimal performance and product quality. The conventional approach to optimizing temperature controller parameters involves manual tuning, which can be time-consuming, labor-intensive, and often lacks precision. This paper introduces an innovative methodology for optimizing the parameters of a temperature controller by integrating statistical methods in the preparation of the experimental plan utilized by neural networks. The integration of statistical techniques in designing the experimental framework enhances the efficiency of data collection, providing a robust foundation for subsequent analysis. The neural network leverages this well-structured dataset to model and optimize the temperature controller parameters, resulting in improved precision and performance. The synergistic integration of statistical methods and neural networks not only streamlines the optimization process but also enhances the reliability of the temperature control system. The effectiveness of the proposed approach is demonstrated through case studies on the Procon level/flow and temperature 38-003 process. The results show significant improvements in temperature control performance, with reduced process variability and faster response times.

Back-propagation ANN to Predict Cleanliness and Quality of Cotton Spinning Preparatory Output: A Comprehensive Research

Background: Modern spinning preparatory has undergone drastic technological changes, but still, individual’s expertise-based decisions govern the complex and non-linear multivariant relationships prevailing amongst raw material (cotton) variables, machine variables, process variables (waste), and product (card sliver) quality. The scientifically precise prediction regarding the cleanliness and quality of card sliver and waste control for the given inputted cotton variables processed on the state-of-the-art machinery setup without waiting for the production and testing of card sliver is still impossible. Methods: The present work describes the use of Aritificial Neural Networks (ANN) for ruling out these limitations on scientific grounds. A complex system targeted at ANN was developed using the "newff" function on the mill's five-year database. Single-group ANN was initially designed to determine the influence of inherent variations in raw cotton fibre properties and trash content on blow room and card performance. A multi-group approach of ANN was developed at a later stage to define the influence of complex interactions amongst various fibre properties on three main quality measures considered at blow room and carding, viz., i) influence of blow room and card on fibre length properties, ii) fibre damage at blow room or improvement at card, and iii) degree of cleanliness of the output material. Results: Reverse modelling for both groups was also successfully designed to demarcate feed cotton quality and cleanliness requirements for targeted blow room or card cleaning performance. Conclusion: A high level of positive endurance was observed for all ANNs. Multigroup networking has proven to be more precise than single group networking.

Utilization of Bamboo (Bambusa vulgaris) Shoots in Fresh Pasta Noodle Production

This study aimed to investigate the sensory acceptability of fresh pasta noodles made from bamboo (Bambusa vulgaris) shoots, incorporating different proportions at 0% (control), 25%, 50%, 75%, and 100%. The sensory acceptability of the treatments was evaluated in terms of aroma, texture, appearance, and taste, as well as their overall acceptability. The study also analyzed the significant differences in sensory qualities between the experimental treatments and compared them with the control. A completely randomized design was employed, involving sixty (60) evaluators. The results indicated that the inclusion of bamboo shoot in the noodle mixture adversely affected the sensory quality, with these negative effects intensifying at higher bamboo shoot proportions. In terms of aroma, texture, appearance, and taste, the differences among the experimental treatments, with the exception of the control treatment, were not statistically significant. However, significant differences were observed in these sensory aspects when comparing the control treatment to the experimental treatments. In conclusion, the research suggests that even small quantities of high-nutritional-value bamboo shoot flour can negatively impact product quality. Future studies should focus on improving the sensory quality and shelf life of these noodles, while also exploring methods to reduce production costs.

Social Media Content, Customer Experience, Product Quality, and Purchase Decisions

ABSTRAKAnalisis keputusan berlangganan bisnis perlu dilakukan untuk mendapatkan strategi pemasaran yangtepat. Banyak sekali platform digital yang saat ini ada, dimana salah satu yang paling sukses dan banyakdigunakan oleh orang Indonesia diantara kompetitor-kompetitor lainnya di dunia industri Video on Demandadalah Netflix. Penelitian ini bertujuan untuk menganalisis adakah pengaruh perilaku konsumen, citra merek,dan minat pembelian pada Keputusan Berlangganan aplikasi Netflix. Populasi pada penelitian ini adalahpelanggan dan/atau pengguna aplikasi Netflix yang tinggal di Area Jabodetabek yang dilakukan denganmetode purposive sampling dan terkumpul 100 responden. Penelitian diolah dengan bantuan softwareSmartPLS 3.0 dan didapatkan hasil (1) Perilaku konsumen berpengaruh positif dan tidak signifikan dengankoefisien 0,071 terhadap Keputusan Berlangganan, (2) Citra Merek berpengaruh positif dan signifikandengan nilai koefisien 0,293 terhadap Keputusan Berlangganan, (3) Minat Pembelian berpengaruh positif dansignifikan dengan koefisien 0,430 terhadap Keputusan Berlangganan. Adapun kontribusi secara bersama-sama variabel perilaku konsumen, citra merek, dan minat pembelian yang ditunjukkan nilai adjusted R Squaresebesar 50% dan sisanya sebesar 50% dipengaruhi oleh variabel lain diluar model dari penelitian ini.Kata kunci : perilaku konsumen, citra merek, minat pembelian, dan keputusanberlangganan.ABSTRACTAnalysis of business subscription decisions needs to be done to get the right marketing strategy. Manydigital platforms currently exist, and one of the most successful and widely used by Indonesians among othercompetitors in the Video on Demand industry is Netflix. This study aims to analyze whether there is aninfluence of consumer behavior, brand image, and purchase intention on the purchase decision for the Netflixapplication. The population in this study are subscribers and/or users of the Netflix application who live in theJabodetabek area. The study was carried out using a purposive sampling method and collected 100respondents. The research was processed with the help of SmartPLS 3.0 software, and the results wereobtained: (1) Consumer behavior has a positive and insignificant effect with a coefficient of 0.071 onpurchasing decisions, (2) Brand image has a positive and significant effect with a coefficient value of 0.293on purchasing decisions, (3) Purchase intention has a positive and significant effect with a coefficient of 0.430on purchasing decisions. The joint contribution of the variables of consumer behavior, brand image, andpurchase intention is shown by the adjusted R Square value of 50% and the remaining 50% is influenced byother variables outside the model of this study.Keyword : consumer behavior, brand image, purchase intention and subscription decision

Incorporating Culture-Independent Methods to Identify Net Syndrome-Associated Fusarium Species in Peanuts

Peanuts ( Arachis hypogaea) are of significant agricultural importance due to their versatile uses, providing a valuable source of edible oil and protein-rich food products and serving in industrial applications. Peanuts are susceptible to various diseases, one of them being net syndrome, a poorly understood threat triggered by an undefined causal agent, with symptoms including black coloring and lesions of the peanut pod that affect product quality. In this study, amplicon sequencing was harnessed to explore the fungal and bacterial populations associated with the syndrome. Using this approach, we identified a specific Fusarium sp. amplicon sequence variant that demonstrated a significant correlation with the presence of net syndrome symptoms in both young and mature peanuts. This finding was further validated by Koch's postulates testing, including isolation, cultivation, and application of this strain to corroborate its involvement in net syndrome in peanuts. Our findings contribute to a better understanding of the interactions between peanuts and their microbial communities and to identification of the previously undetermined agent involved in net syndrome and the etiology of the disease.

3D Printing-as-a-Service: An Economic Analysis of Pricing and Cocreation

Three-dimensional (3D) printing technology has opened up possibilities for product design collaborations between device providers and customers. To enable an environment of cocreation, device providers are now renting 3D printers via the 3D-as-a-Service (3DaaS) model. Although prior research has examined pricing and quality issues in the traditional manufacturing setup, these studies have not analyzed such decisions in the 3D printing supply chain setting, where end users possess the ability to customize product designs. Therefore, several important questions remain unanswered from the perspective of the 3D printing device provider. For example, what is the appropriate pricing model for providing 3DaaS? How do factors such as the extent of design customization and the complexity influence the pricing strategy of the 3DaaS firm? Our analysis shows that if the customers’ impact on the product quality is relatively high or low, the pay-per-build pricing model generates a higher profit than the fixed-fee pricing model. Interestingly, we also find that if customers frequently print highly intricate product designs, the firm might choose the pay-per-build pricing model, only if the likelihood of design failure for these complex structures is low. Otherwise, the firm might opt for the fixed-fee pricing model.

Integrating effective journal club activities into knowledge management processes to enhance evidence-based practice, service quality, research skills, and innovation among nurses: A literature review

In a rapidly emerging world, knowledge management capabilities, including knowledge creation, acquisition, sharing, and utilization, become more critical for organizational change, growth, and competitiveness. Therefore, this article argues that organizations should consider implementing effective journal club meetings as an opportunity to acquire external knowledge, evaluate and integrate new knowledge into previous existing knowledge, and disseminate and utilize new knowledge to enhance product or service quality, innovation, and the performance of an organization. The article reviews relevant literature, proposes a framework for conducting effective journal club meetings, and aligns those activities with the knowledge management processes. The article proposes a framework for conducting effective journal club meetings and a process that integrates both journal club activities and the knowledge management process. By adopting this framework, journal club activities would be more effective in developing new knowledge management capabilities among individual members and enhancing organizational performance, i.e., implementing evidence-based practices (EBP), improving service quality, and producing research.

Industrial automation and product quality: the role of robotic production transformation

ABSTRACT We investigate the impact of industrial automation, specifically robots, on product quality in international trade. By analysing detailed data from Chinese listed firms, we examine how the adoption of robots is associated with higher product quality compared to that of nonrobot users. This effect is more pronounced among heterogeneous products and in ordinary trade patterns. We identify several mechanisms through which robots contribute to product quality improvements, including resource reallocation, adaptability to complex production processes, and enhancement of input quality. Moreover, we demonstrate that replacing low-skilled labour with complex robots and employing high-skilled labour to collaborate with robots improved product quality, confirming that robotic displacement and reinstatement effects generate better product quality upgrading. Overall, our empirical evidence supports the positive influence of robot adoption on product quality and provides insights into the mechanisms underlying robotic production transformation.

An integrated hybrid approach for assembly tolerance transfer and allocation

Purpose This study aims to develop an optimal tolerance allocation strategy involves integrating the unique transfer (UT) approach and the difficulty coefficient evaluation (DCE) routine in an interactive hybrid method. This method combines the strengths of both UT and DCE, ensuring simultaneous utilization for enhanced performance. The proposed tolerancing model manifests an integrated computer-aided design (CAD) tool. Design/methodology/approach By combining UT and DCE based on failure mode, effects and criticality analysis (FMECA) tool and the Ishikawa diagram, the proposed collaborative hybrid tool ensures an efficient and optimal tolerance allocation approach. The integration of these methodologies not only addresses specific transfer challenges through UT but also conducts a thorough evaluation of difficulty coefficients via DCE routine using reliability analysis tools as FMECA tool and the Ishikawa diagram. This comprehensive framework contributes to a robust and informed decision-making process in tolerance allocation, ultimately optimizing the design and manufacturing processes. Findings The presented methodology is implemented with the aim of generating allocated tolerances that align with specific difficulty requirements, facilitating the creation of a mechanical assembly characterized by high quality and low cost. To substantiate and validate the conceptual framework and methods, an integrated tool has been developed, featuring a graphical user interface (GUI) designed in MATLAB. This interface serves as a platform to showcase various interactive and integrated tolerance allocation approaches that adhere to both functional and manufacturing prerequisites. The proposed integrated tool, designed with a GUI in MATLAB, offers the capability to execute various examples that effectively demonstrate the benefits of the developed tolerance transfer and allocation methodology. Originality/value The originality of the proposed approach is the twining between the UT and DCE simultaneous in an integrated and concurrent tolerance transfer and allocation model. Therefore, the proposed approach is named an integrated CAD/tolerance model based on the manufacturing difficulty tool. The obtained results underscore the tangible advantages stemming from the integration of this innovative tolerance transfer and allocation approach. These benefits include a notable reduction in total cost and a concurrent enhancement in product quality.

In-situ tool wear condition monitoring during the end milling process based on dynamic mode and abnormal evaluation

Rapid tool wear conditions during the manufacturing process are crucial for the enhancement of product quality. As an extension of our recent works, in this research, a generic in-situ tool wear condition monitoring during the end milling process based on dynamic mode and abnormal evaluation is proposed. With the engagement of dynamic mode decomposition, the real-time response of the sensing physical quantity during the end milling process can be predicted. Besides, by constructing the graph structure of the time series and calculating the difference between the predicted signal and the real-time signal, the anomaly can be acquired. Meanwhile, the tool wear state during the end milling process can be successfully evaluated. The proposed method is validated in milling tool wear experiments and received positive results (the mean relative error is recorded as 0.0507). The research, therefore, paves a new way to realize the in-situ tool wear condition monitoring.

Empirical comparison of assembly complexity assessment approaches in manufacturing

AbstractInvestigating assembly complexity is a continuing concern within the manufacturing field, as it may impact the quality and costs of products. A growing body of literature is aimed at developing novel and reliable methods to assess assembly complexity. The first aim of this paper is to provide an extensive literature review, identifying the main approaches to this problem. Three main approaches emerged: product-centred approach, information-centred approach and system-centred approach. A second goal is to conduct a comparative analysis of these approaches, highlighting their advantages and limitations and providing guidance for process and product designers seeking to control assembly complexity. For each approach, a representative method was chosen, analysed in detail, and applied to five different real products. As concluding findings it was observed that product-centred approaches provide a more objective analysis, focusing strictly on product features. On the other hand, information-centred approaches focus on quantity and variety of information handled by assembly operators, thus proposing a valuable link between complexity and effort required. Finally, system-centred approaches provide a holistic assessment of assembly complexity which is typically only qualitative.

Influence of fermentation conditions, and the blends of sorghum and carrot pulp supplementation on the nutritional and sensory quality of tef injera

Tef [Eragrostis tef (Zucc.) Trotter], an ancient cereal primarily grown in Ethiopia, is becoming increasingly popular worldwide due to its high iron content and gluten-free nature. However, it has been reported that injera produced only with tef flour lack certain vital nutrients. Therefore, this specific study was conducted to supplement tef injera with other food materials of better nutritional value and compensate its expensive market price with sorghum cereal flour. The effect of fermentation conditions, and the sorghum and carrot pulp blending ratio on the nutritional value and sensory quality of tef injera was investigated. The factorial approach of the experimental design was conducted considering the nutritional value and sensory quality of the injera made of three main blending ratios of tef, sorghum, and carrot (60% tef: 30% sorghum: 10% carrot pulp, 45% tef: 45% sorghum: 10% carrot pulp and 30% tef: 60% sorghum: 10% carrot pulp) as experiential variables. The raw materials and injera were characterised for their proximate composition, physicochemical property, mineral composition, microbial analysis, and sensory attributes, using standard methods. The results of the study show that fermentation conditions and blending ratios have a significant effect on the nutritional, anti-nutritional, mineral content, microbial quality, and sensory properties of blended injera products, where higher values of ash, crude protein, crude fat, Total titratable acidity (TTA), Fe, Zn, and Ca (2.30%, 11.34%, 2.62%, 3.53, 32.97 mg/100 g, 2.98 mg/100 g and 176.85 mg/100 g, respectively) were analyzed for the co-fermented injera sample. In addition, a lower microbial count was observed in co-fermented injera samples, whereas microbial counts in injera samples prepared from carrot pulp-supplemented dough after the co-fermentation of tef and sorghum flours were observed to be higher. The injera product made using blending ratio of 60% tef: 30%sorghum: 10% carrot co-fermented was found to be the optimum result due to its very good nutritional improvement (i.e., reduction of some anti-nutritional factors, microbial contents, pH and increased contents of some minerals, crude protein, crude fat, TTA and improved most of the sensory quality of the supplemented injera product). According to this study, sorghum and carrot supplementation on tef could improve the nutritional value of injera while also providing an instant remedy for the growing price of tef.

Comparison of the H2O, HDO and δD stratospheric climatologies between the MIPAS-ESA V8, MIPAS-IMK V5 and ACE-FTS V4.1/4.2 satellite datasets

Abstract. Variations in the isotopologic composition of water vapour are fundamental for understanding the relative importance of different mechanisms of water vapour transport from the tropical upper troposphere to the lower stratosphere. Previous comparisons obtained from observations of H2O and HDO by satellite instruments showed discrepancies. In this work, newer versions of H2O and HDO retrievals from Envisat/MIPAS and SCISAT/ACE-FTS are compared. Specifically, MIPAS-IMK V5, MIPAS-ESA V8 and ACE-FTS V4.1/4.2 for the common period from February 2004 to April 2012 are compared for the first time through a profile-to-profile approach and comparison based on climatological structures. The comparison is essential for the scientific community to assess the quality of new satellite data products, a necessary procedure to validate further scientific work. Averaged stratospheric H2O profiles reveal general good agreement between 16 and 30 km. Biases derived from the profile-to-profile comparison are around zero between 16 and 30 km for MIPAS-IMK and ACE-FTS comparison. For HDO and δD, low biases are found in the MIPAS-ESA and ACE-FTS comparison in the same range of altitudes, even if associated with a larger de-biased standard deviation. The zonally averaged cross sections of H2O and HDO exhibit the expected distribution that has been established in previous studies. For δD the tropical depletion in MIPAS-ESA occurs at the top of the dynamical tropopause, but this minimum is found at higher altitudes in the ACE-FTS and MIPAS-IMK dataset. The tape recorder signal is present in H2O and HDO for the three databases with slight quantitative differences. The δD annual variation for ACE-FTS data and MIPAS-ESA data is weaker compared to the MIPAS-IMK dataset, which shows a coherent tape recorder signal clearly detectable up to at least 30 km. The observed differences in the climatological δD composites between databases could lead to different interpretations regarding the water vapour transport processes toward the stratosphere. Therefore, it is important to further improve the quality of level 2 products.

Utilizing Deep Learning for Defect Inspection in Hand Tool Assembly.

The integrity of product assembly in the precision assembly industry significantly influences the quality of the final products. During the assembly process, products may acquire assembly defects due to personnel oversight. A severe assembly defect could impair the product's normal function and potentially cause loss of life or property for the user. For workpiece defect inspection, there is limited discussion on the simultaneous detection of the primary kinds of assembly anomaly (missing parts, misplaced parts, foreign objects, and extra parts). However, these assembly anomalies account for most customer complaints in the traditional hand tool industry. This is because no equipment can comprehensively inspect major assembly defects, and inspections rely solely on professionals using simple tools and their own experience. Thus, this study proposes an automated visual inspection system to achieve defect inspection in hand tool assembly. This study samples the work-in-process from three assembly stations in the ratchet wrench assembly process; an investigation of 28 common assembly defect types is presented, covering the 4 kinds of assembly anomaly in the assembly operation; also, this study captures sample images of various assembly defects for the experiments. First, the captured images are filtered to eliminate surface reflection noise from the workpiece; then, a circular mask is given at the assembly position to extract the ROI area; next, the filtered ROI images are used to create a defect-type label set using manual annotation; after this, the R-CNN series network models are applied to object feature extraction and classification; finally, they are compared with other object detection models to identify which inspection model has the better performance. The experimental results show that, if each station uses the best model for defect inspection, it can effectively detect and classify defects. The average defect detection rate (1-β) of each station is 92.64%, the average misjudgment rate (α) is 6.68%, and the average correct classification rate (CR) is 88.03%.

Irreversible temperature indicator based cellulose membranes conjugated with leuco‐dye pigment

AbstractThis research focuses on the development of thermochromic membranes made of cellulose acetate (CA) for temperature monitoring of sensitive food products. Two dual TC membranes developed for the control of different temperature ranges were formulated using a three‐component system: a leuco‐dye membrane (crystal violet lactone, CVL) integrated with an acidic membrane containing the color developer (salicylic acid) and the acidic solvent with different melting points (decanoic acid, DA, or methacrylic acid, MA). The CVL membrane, together with the DA membrane, showed an irreversible color change when exposed to 35°C, which was facilitated by the melting of DA. The CVL membrane also underwent an irreversible color change when exposed to 15°C together with the MA membrane. The membranes were characterized in detail using scanning electron microscopy. The evaluation of color changes, reproducibility, specificity, and stability ensured the practical suitability of these membranes. Overall, this innovative approach has proven to be a reproducible, sustainable, cost‐effective method to produce irreversible colorimetric temperature sensors. These sensors have significant potential for applications in the food and pharmaceutical industries and offer a promising way to improve product safety and quality.

Hydrothermal liquefaction of composite household waste to biocrude: the effect of liquefaction solvents on product yield and quality.

The hydrothermal liquefaction (HTL) of composite household waste (CHW) was investigated at different temperatures in the range of 240-360 °C, residence times in the range of 30-90 min, and co-solvent ratios of 2-8 ml/g, by utilising ethanol, glycerol, and produced aqueous phase as liquefaction solvents. Maximum biocrude yield of 46.19% was obtained at 340 °C and 75 min, with aqueous phase recirculation ratio (RR) of 5 ml/g. The chemical solvents such as glycerol and ethanol yielded a biocrude percentage of 45.18% and 42.16% at a ratio of 6 ml/g and 8 ml/g, respectively, for 340 °C and 75 min. The usage of co-solvents as hydrothermal medium increased the biocrude yield by 35.30% and decreased the formation of solid residue and gaseous products by 19.82% and 18.74% respectively. Also, the solid residue and biocrude obtained from co-solvent HTL possessed higher carbon and hydrogen content, thus having a H/C ratio and HHV that is 1.01 and 1.23 times higher than that of water as hydrothermal medium. Among the co-solvents, HTL with aqueous phase recirculation resulted in higher carbon and energy recovery percentages of 9.36% and 9.78% for solid residue and 52.09% and 56.75% for biocrude respectively. Further qualitatively, co-solvent HTL in the presence of obtained aqueous phase yielded 33.43% higher fraction of hydrocarbons than the pure water HTL and 7.70-17.01% higher hydrocarbons when compared with ethanol and glycerol HTL respectively. Nitrogen containing compounds, such as phenols and furfurals, for biocrudes obtained from all HTL processes, were found to be present in the range of 8.30-14.40%.

How semiotic product packaging, brand image, perceived brand quality influence brand loyalty and purchase intention: a stimulus-organism-response perspective

PurposeThe present study, underpinned by the stimulus-organism-response (SOR) theory, aims to examine the impact of packaging semiotics on brand image, perceived brand quality, brand loyalty and purchase intention of well-established food brands.Design/methodology/approachA self-administered questionnaire was disseminated to participants residing in the Lucknow region of India. We conducted an experiment in which 374 participants evaluated the factors on a stimulus (chips packaging) using an online survey. Collected data were analysed through structural equation modelling (SEM).FindingsThe result suggests that packaging semiotics exhibits a positive influence on brand image and perceived brand quality of consumers. The brand image significantly impacts brand loyalty and consumers’ purchase intention. In addition, the perceived brand quality has a positive significant impact on brand loyalty, but a negative and insignificant influence on purchase intention. The results show that both brand image and perceived brand quality significantly mediate the relation between packaging semiotics and brand loyalty. Brand image significantly mediates but perceived brand quality does not mediate the relation between packaging semiotics and purchase intention.Practical implicationsThe results of the study will assist food brands in determining how to utilise semiotics in packaging to positively influence brand image, perceived brand quality, brand loyalty and consumers’ intent to purchase.Originality/valueThe study is unique in the sense that it assesses the role of packaging semiotics as antecedent in mapping of brand loyalty and purchase intention through brand image and perceived product quality. This study takes a lead as these constructs have been less explored relatively from the lens of packaging semiotics in an emerging Asian market.

Unfair commercial practices towards consumers in the Hungarian food industry

Unfair commercial practices in the food industry can include actions and practices by traders or producers that mislead consumers about the true characteristics, quality, or price of products. For example, if a producer does not accurately and transparently list the composition of products, or if advertisements contain false or misleading information about products, or if inappropriate product quality is concealed, or if promised benefits of products are not realised, or if consumers are unfairly persuaded to purchase products. It is important to note that all traders and producers must comply with consumer protection rules. If any unfair commercial practices are observed, consumers can legitimately file a complaint with the Consumer Protection Authority or the Hungarian Competition Authority. Unfair commercial practices can be a serious problem for consumers as they mislead them about the true characteristics of products, making it difficult to make informed purchasing decisions. Therefore, it is important for consumers to be informed about the true composition and quality of products in order to avoid falling victim to unfair commercial practices. Through various legal cases, I demonstrate how important it is for consumers to be fully informed and aware of their rights. Additionally, I illustrate how investigating different complaints can have an impact on preventing unfair commercial practices.

Price regulation, network externality, and product innovation strategies: A dynamic analysis

AbstractFor many high‐tech and Internet‐related products, consumers' utility depends partly on the scale of user groups, which is called network externality. This phenomenon plays a crucial role in shaping firms' innovation strategies, especially in markets with price regulation. This paper aims to investigate a monopolist's dynamic product innovation problem in a price‐regulated market exhibiting network externality. We identify the sufficient conditions guaranteeing the existence of optimal steady‐state equilibrium. Our analysis mainly shows the following: (i) the product quality and network size move in opposite directions along the path to the steady‐state equilibrium; (ii) the equilibrium result of product innovation increases with the regulated price but decreases with the intensity of network externality; (iii) the social‐welfare maximizing path of product innovation can be replicated by a dynamic price regulation regime, involving a premium on quality and a premium or a penalty on network size. Numerical experiments are performed to characterize the dynamic patterns of product innovation. We find that firms with high brand power prefer adopting mild product innovation strategy while for firms with low brand power, almost constant high‐quality strategy is better.