Consumer Goods Research Articles

E-Mart : (Wholesale E-Commerce Platform)

The E-Mart project is a wholesale e-commerce platform designed to bridge the gap between manufacturers, distributors, and retailers by providing a seamless online marketplace. In an era where digital transformation is reshaping industries, wholesale commerce remains a critical area that demands modernization. E-Mart addresses the inefficiencies of traditional wholesale operations by offering a user-friendly, scalable, and secure platform where bulk buyers and sellers can interact and transact with ease. This platform not only simplifies the procurement process but also opens new business opportunities by leveraging technology to create a transparent, efficient, and cost-effective supply chain. The core objective of E-Mart is to streamline B2B (business-to-business) transactions, offering a robust platform for wholesale buyers to access a wide range of products directly from manufacturers and distributors. Key features of the platform include product listing, price comparison, bulk order management, secure payment gateways, and logistics integration for tracking shipments. Sellers can manage inventory, set pricing, and receive real-time analytics to optimize their business strategies, while buyers benefit from competitive pricing, bulk discounts, and an easy-to-navigate interface that reduces the complexity of large-scale procurement. To develop this platform, we employed agile development methodologies and open-source technologies to ensure flexibility, scalability, and security. The system architecture is designed to handle large volumes of transactions and concurrent users while ensuring data integrity and protection through encryption protocols. The backend integrates with various APIs for payment processing, shipping, and inventory management, while the frontend focuses on providing a clean, intuitive user experience. A pilot implementation of E-Mart was conducted with select wholesalers and retailers in different sectors, including electronics, consumer goods, and textiles. The results showed significant improvements in order accuracy, reduced lead times, and cost savings for both buyers and sellers. Furthermore, feedback from early adopters has been overwhelmingly positive, highlighting the platform's potential to transform wholesale e-commerce. In conclusion, E-Mart presents a comprehensive solution to the challenges faced in the wholesale market by integrating technology-driven innovations with industry best practices. As the platform evolves, future enhancements will include AI-driven analytics, dynamic pricing models, and further customization options to enhance user experience and profitability..

When Should Incumbent Consumer Goods Producers Ally with Digital Platforms?

Physical goods producers routinely collaborate with digital platforms to extend their distribution capabilities. They usually realize that digital platform firms differ from them in their strategies and capabilities, and that significant opportunities arise from innovating digital platforms being able to collect, analyze, and leverage behavioral customer data related to the consumption experience. However, collaborating with digital platforms is likely to put competitive pressure on the incumbent’s margins, and, in extremis, encourage entry by the platform into the incumbent’s business. These threats can be moderated by limiting access to the incumbent’s technology and supply chain, or by building an in-house digital platform.

Differences between Intellectual Capital and Size as a Moderating Variable in Manufacturing Companies Before and After The Covid-19 Pandemic

This research proves the concept (proof-of-concept) of important functions and/or characteristics analytically and experimentally. The aim of this research is to determine the effect of intellectual capital on financial performance with size as a moderating variable in manufacturing companies amidst the conditions before and after the Covid-19 pandemic in 2018 - 2021. This research is quantitative research with secondary data. The population in this research are manufacturing companies listed on the Indonesia Stock Exchange (BEI) in the research years 2018 to 2021. This research uses a purposive sampling technique to complete sample selection and produce samples from 39 manufacturing companies in the consumer goods sector for the period 2018 - 2021. Testing hypotheses and data analysis using multiple linear regression and moderated regression analysis (MRA) with the help of SPSS version 22. The results of the study are as follows, there is no difference between before and after the pandemic for VACA, VAHU, STVA, and VAIC. While for those moderated by size for VACA, VAHU, STVA, and VAIC there is no difference between before and after the pandemic

Development of per Capita GDP Forecasting Model Using Deep Learning: Including Consumer Goods Index and Unemployment Rate

In the 21st century, the increasing complexity and uncertainty of the global economy have heightened the need for accurate economic forecasting. Per capita GDP, a critical indicator of living standards, economic growth, and productivity, plays a key role in government policy-making, corporate strategy, and investor decisions. However, predicting per capita GDP poses significant challenges due to its sensitivity to various economic and social factors. Traditional methods such as statistical analysis, regression, and time-series models have shown limitations in capturing nonlinear interactions and volatility of economic data. To address these limitations, this study develops a per capita GDP forecasting model based on deep learning, incorporating key macroeconomic variables—the Consumer Price Index (CPI) and unemployment rate (UR)—to enhance predictive accuracy. This study employs five deep-learning regression models (RNN, LSTM, GRU, TCN, and Transformer) applied to real and placebo datasets, each incorporating combinations of CPI and UR. The results demonstrate that deep learning models can effectively capture complex, nonlinear relationships in economic data, significantly improving predictive accuracy compared to traditional models. Among the models, the Transformer consistently achieves the highest R-squared and lowest error values across various metrics (MSE, RMSE, and MSLE), indicating its superior ability to model intricate economic patterns. In addition, including CPI and UR as additional predictors enhances model robustness, with the TCN and Transformer models showing particularly strong performance in capturing short-term economic fluctuations. The findings suggest that the deep learning models, especially the Transformer, offer valuable tools for policymakers and business leaders, providing reliable GDP forecasts that support economic decision-making, resource allocation, and strategic planning. Academically, this study advances the understanding of deep learning applications in economic forecasting, particularly in integrating significant macroeconomic variables for enhanced predictive performance. The developed model is a foundation for informed economic policy and strategic decisions, offering a robust and actionable framework for managing economic uncertainties. This research contributes to theoretical and applied economics, providing insights that bridge academic innovation with practical utility in economic forecasting.

Marketing Mix and Consumer Purchase Decision of Fast-Moving Consumer Goods (FMCG) in Akwa Ibom State, Nigeria

This study was conducted to examine the effect of marketing mix on the consumer purchase decision of fast-moving consumer goods (FMCG) in Akwa Ibom State, Nigeria. The survey research design was used in this study. Data for the study were obtained through a structured questionnaire administered to the respondents. The population of the study comprised all the consumers of fast-moving consumer goods (FMCG) in Akwa Ibom State. The sample size of 308 respondents were selected using convenience sampling technique. Four hypotheses were formulated and tested using Spearman Correlation at 0.05 level of significance. The findings of the study revealed that there is a positive and significant relationship between marketing mix-product, price, place, promotion and consumer purchase decision of fast-moving consumer goods (FMCG) in Akwa Ibom State, with the correlation coefficient (r = 0.479), (r =0.573), (r = .0.720) and (r = 0.623) respectively at the significant value of 0.000 (p>0.05). Therefore, it is concluded that marketing mix plays an important role in influencing the consumer purchase decision of fast-moving consumer goods (FMCG).

Can the Dimensional Optimisation of 3D FDM-Manufactured Parts Be a Solution for a Correct Design?

Additive manufacturing technology, also known as 3D printing, has emerged as a viable alternative in modern manufacturing processes. Unlike traditional manufacturing methods, which often involve complex mechanical operations that can lead to errors and inconsistencies in the final product, additive technology offers a new approach that enables precise layer-by-layer production with improved geometric accuracy, reduced material consumption and increased design flexibility. Geometrical accuracy is a critical issue in industries such as aerospace, automotive, medicine and consumer goods, hence the importance of the following question: can the dimensional optimisation of 3D FDM-manufactured parts be a solution for correct design? This paper presents a complex study of model parts printed from four common polymers used in fused deposition modelling (FDM) additive technology, namely ABS (acrylonitrile-butadiene-styrene), PLA (polylactic acid), HIPS (high-impact polystyrene) and PETG (polyethylene terephthalate glycol). The results of the methodology used highlight the dimensional changes that need to be made at the design stage, depending on the direction of printing and the type of geometric elements in the final part.

Changes in household purchasing of soft drinks following the UK soft drinks industry levy by household income and composition: controlled interrupted time series analysis, March 2014 to November 2019

BackgroundThe WHO recommends taxes on sugar sweetened beverages (SSBs) to improve population health. We examined changes in volume of and amount of sugar in purchases of soft drinks according to...

Revitalization Practices of World Cultural Heritage: A Case Study of Yungang Grottoes

In contemporary society, the consumption of symbols and meanings has become the core of postmodern society, and engaging with cultural heritage has become an important way for people to seek connections with society and represent their own identities. Under the influence of consumerism, cultural heritage has been packaged as consumable goods, transforming into a public history belonging to the market economy. Public history enhances communication across all levels of society and cultural heritage, thereby generating diverse social needs. This process leads to new developments in cultural heritage, transforming the value of existing art, culture, history, and other aspects into economic value for consumption. This is a new social phenomenon that combines art and sociology, and it is also a popular trend in contemporary society. This study takes the Yungang Grottoes as a case, employing field investigation, observation, and literature analysis among qualitative research methods to study the historical consumption forms of World Cultural Heritage in the context of modern society. The study found that World Cultural Heritage contains unique cultural values, and under the influence of historical consumerism, the value system of the heritage is expanded. The rational utilization of heritage becomes the key direction for sustainable development of heritage, enriching the forms of historical consumption of cultural heritage is the key force for the revitalization of cultural heritage. The study has universality and provides important reference value for the revitalization of cultural heritage in other regions of the world.

Evaluating the Sensitivity of Consumption towards the Price of Components of the Consumer Basket

This study investigates Jordanian market demand in terms of consumption sensitivity to changes in consumer basket component prices. The researchers anticipate that the study, through analysing demand functions and elasticities, will help to add qualitative insights to the Jordanian economic database. The researchers statistically derived coefficients based on information about the consumer basket used to calculate the standard price index using simple linear logarithmic regression. Using this methodology, the research study has produced several findings, including: There are two types of consumer basket components: elastic and inelastic. A strong divide occurs at the level of the consumer basket between critical first-tier goods and second-tier consumer goods. Consumption sensitivity assessments can influence governmental decisions about tax policy as well as businessmen decisions regarding production volume and output capability. The price elasticity of demand for chickpeas, cakes, green olives, black olives, and kerosene is 5%, 17.8%, 6.9%, 3.7%, and 1.2%, respectively.

From Waste to Innovation: A Circular Economy Approach for Tissue Engineering by Transforming Human Bone Waste into Novel Collagen Membranes.

The aim of the circular economy is to treat waste as a valuable raw material, reintegrating it into the industrial economy and extending the lifecycle of subsequent products. Efforts to reduce the production of hard-to-recycle waste are becoming increasingly important to manufacturers, not only of consumer goods but also of specialized items that are difficult to manufacture, such as medical supplies, which have now become a priority for the European Union. The purpose of the study is to manufacture a novel human-purified type I collagen membrane from bone remnants typically discarded during the processing of cortico-cancellous bones in tissue banks and to evaluate its mechanical properties and effectiveness in regenerating bone-critical mandibular defects in rabbits. To prepare the novel membrane, cortico-cancellous bone chip samples from a local tissue bank were processed to isolate collagen by demineralization under agitation in HCl, cast into a silicone mold, and air-dried at room temperature and UV irradiation. The average thickness of the four batches analyzed by SEM was 37.3 μm. The average value of Young's modulus and tensile strength obtained from the specimens was 2.56 GPa and 65.43 Mpa, respectively. The membrane's efficacy was tested by creating a critical bicortical and bilateral osteoperiosteal defect in rabbit mandibles. The right-side defects were covered with the collagen membrane, while the left-side defects were left untreated as a control. Nine weeks post-surgery, clinical, radiological, and histological analyses demonstrated new bone formation in the treated areas, whereas the control sites showed no bone regeneration. This innovative approach not only contributes to sustainability in healthcare by optimizing biological waste but also exemplifies efficient resource use in line with the circular economy, offering a cost-effective, biocompatible option that could benefit national health systems.

Features of Implementing Parallel Import in The Russian Federation under the Conditions of Sanctions

This article analyzes the specifics of parallel imports in the Russian Federation under sanctions imposed by a number of countries. In conditions of limited access to traditional supply channels for goods and technologies, parallel imports are becoming an important tool for providing the domestic market with necessary products and solving the problem of replacing unavailable goods. The author examines the legal aspects of parallel imports, including changes in legislation that temporarily allow the import of products without the consent of the copyright holder. This helps to mitigate the impact of sanctions and avoid shortages in a number of key industries, such as electronics, household appliances, cars and other consumer goods. Particular attention is paid to the economic consequences of parallel imports. On the one hand, it helps stabilize prices for scarce goods and reduces pressure on consumers. On the other hand, there are risks associated with the quality and safety of products imported through alternative channels. The possible consequences for copyright holders and international companies whose interests may be infringed as a result of such deliveries are also discussed. The article provides examples of the use of parallel imports in Russia, and analyzes the main risks and benefi ts for business and the economy as a whole. In conclusion, the author suggests possible scenarios for the development of parallel imports in the context of ongoing sanctions pressure, assessing its prospects as a temporary but important mechanism for maintaining economic stability.

Comparative analysis of outsourcing and in house warehouse management system to improve productivity and stock accuracy

This study compares the impact of outsourced and in-house Warehouse Management Systems (WMS) on productivity and stock accuracy in the fast-moving consumer goods (FMCG) sector. Data was collected from a logistics services company in Palembang using quantitative methods, including measurements of productivity per person per hour and stock accuracy per SKU. Productivity was assessed based on items processed per unit time, while stock accuracy compared physical stock with system records. Additional data was gathered through a Google Form survey targeting operational staff and warehouse managers to understand the implementation of both WMS models. The survey covered critical processes such as putaway, picking, and inventory, providing insights into operational efficiency and challenges associated with each model. Dummy variable multiple regression was applied to evaluate the performance impact of each WMS model, supplemented by qualitative insights from structured interviews. Findings reveal that WMS in-house is better than outsourcing WMS. While 12.5% of respondents rated the outsourced WMS as inefficient, none reported inefficiencies in the in-house system. Additionally, 62.5% of respondents found the in-house WMS highly effective, citing smoother implementation and higher reliability. The in-house WMS also demonstrated superior operational efficiency, storage accuracy, and responsiveness. It provided better storage location guidance (33.3%) and faster, more accurate operator navigation (26.5%) compared to the outsourced system. Moreover, only 33.3% of respondents noted delays in resolving technical issues with the in-house system, versus 68.8% for the outsourced system. Statistical analysis further supported these findings, showing significant advantages for the in-house WMS in productivity (p=0.068) and stock accuracy (p=0.000). These results highlight the strategic advantages of adopting an in-house WMS, underscoring its role in enhancing operational efficiency and maintaining competitiveness in the dynamic FMCG market.

The Role of Sustainable Packaging in Saudi Arabian Supply Chains FMCG: Analyzing Consumer Acceptance and Marketing Strategies for Enhancing Environmental Impact

Sustainable packaging trends have, therefore, shaped consumers' behavior in the fast-moving consumer goods (FMCG) sector in Saudi Arabia. A quantitative approach has been taken in this present study to test the hypothesis that environmental concern, cost consciousness, and cultural values, along with positive portrayals of sustainable packaging, would influence consumer acceptance and satisfaction and marketing strategies toward the product. By applying partial least squares structural equation modelling (PLS-SEM) to survey data from Saudi consumers, research has demonstrated that environmental concerns drive satisfaction and demand, whereas positive portrayals drive advocacy and consumer perceptions. Other findings point to nuances in the role of cost awareness and cultural values in marketing strategy and brand loyalty. This research provides useful insights to businesses and policymakers on how to combine sustainable practices for environmental impact and consumer engagement in Saudi Arabia.

RFID Unpacked: A Case Study in Employing RFID Tags from Item to Pallet Level

As the use of passive ultra-high frequency (UHF) radio frequency identification (RFID) tags continues to surge in supply chain management, it becomes crucial to optimize their application at various levels of packaging to ensure reliability. These packaging levels play a pivotal role in achieving maximum readability and widespread adoption within the industry. This research paper aims to determine the most suitable passive UHF RFID tag for consumer goods filled with liquid and wrapped in foil packaging. In this study, two distinct RFID tags from separate manufacturers were evaluated. The research focused on critical factors such as reader height, distance, and item configuration across different packaging levels (item, case, and pallet). The results demonstrated that the packaging configuration impacts the readability of RFID tags at each packaging level. Through rigorous testing, it was found that achieving a tag readability rate higher than 99.7% is feasible and readability can be optimized by adjusting the reader position, packaging configuration, and tag design. The optimized configuration and testing platform developed in this study can be used for comparable products in other supply chains such as consumer goods, pharmaceuticals, and food. The results of this study emphasize RFID’s potential to revolutionize supply chain management.

Pengaruh Tarif Pajak dan Kepemilikan Asing terhadap Penerapan Transfer Pricing untuk Penghindaran Pajak

The purpose of this study is to determine the effect of tax rates (X1) and foreign ownership (X2) on the application of transfer pricing (Y) for tax avoidance (Z). Case study of consumer goods manufacturing companies listed on the IDX for the 2017-2021 period. The population of this study was 63 companies in the consumer goods sector and 7 companies were selected as samples according to the criteria in purposive sampling. The analisys technique used in this study is multiple linier analisys, which was previously tested first with the classical assumption test. The results of this study indicate that partially tax rates do not affect transfer priing and foreign ownership partially affects transfer pricing. However, simultaneously does not affect transfer pricing. The correlation coefficient value shows that all independent nvariables have an influence of 76.3 the rest is explained by other variables outside the study. Based on the path analys test, the results show that tax rates affect tax avoidance while foreign ownership and transfer pricing do not affect tax avoidance. The correlation coefficient value shows that tax rates, foreign ownership and transfer pricing on tax avoidance are 67.1 on the next variable, 32,9 the rest is explainedby other variables outside the study.

Changes in Lifestyle Behaviors, Shopping Habits and Body Weight Among Adults in Cyprus and Greece During COVID-19 Lockdown: A Cross-Sectional Study.

Background: During the COVID-19 pandemic, people were asked to stay at home. Places where people interacted such as schools, universities, and cafes were closed, and all gatherings were forbidden. Only stores offering fast-moving consumer goods were open, so citizens could purchase all food categories. The aim of this cross-sectional study was to investigate the effect of the COVID-19 lockdown on the eating and buying habits of consumers in Cyprus and Greece, and any changes in their lifestyles. Methods: An online survey including 1011 participants took place using an electronic questionnaire. Results: The results showed that lockdown significantly affected individuals by increasing weight gain (p < 0.01). The explanatory investigation of related lifestyle habits and nutrition traits showed that the dietary patterns behind these changes included increased meal frequency (p < 0.05)-even without an increased appetite-and subsequent increases in both purchases (p < 0.05) and consumption of several food groups (p < 0.05). Moreover, even though exercise per se was not discontinued due to COVID-19, it was apparent that exercise type was altered to adapt to the relevant restrictions (p < 0.05). Conclusions: In conclusion, the COVID-19 lockdown significantly affected Cypriots and Greeks in many aspects like their eating behavior, food purchasing habits, and lifestyle, all resulting in increased weight and potentially adverse health outcomes.

Challenges of Biological Complexity in the Study of Nanotoxicology.

The scale of nanoparticle use in consumer goods has grown exponentially over several decades owing to the unique properties of materials in this size range. At the same time, well-defined end of life cycle disposal strategies have not been developed for most materials, meaning that we are approaching the potential for a new ecological disaster with the release of millions of metric tons of nanoparticles into the waste stream. The field of nanotoxicology has grown to meet the challenge of investigating the potential hazards of these materials and has already identified toxicity mechanisms that affect multiple tropes of life. However, there are stipulations on how applicable many of these results are to real world applications. These limitations largely arise from the complex network of variables that must be considered during these investigations. Herein, we focus on the challenges posed by the transformations that nanoparticles undergo when they are introduced into a biological environment. For example, biomolecules, such as proteins, rapidly coat nanoparticles with a shell, called a corona, that can modulate the toxicity of the core materials and/or aid its internalization into cells. As such, unlike in the evaluation of small molecule toxicity, one cannot assume that they know the composition of the nanoparticle-biomolecule species at any given time. This additional layer of complication, as well as the noncovalent nature of the corona, have made it difficult to identify consistent toxicity trends. In this Perspective, we highlight current analysis strategies and the difficulties in studying nanotoxicity, recent advances to aid in these studies, and efforts to reduce nanotoxicity and outline remaining challenges.

Analisis Empiris Agresivitas Penghindaran Pajak Dalam Konteks Tanggung Jawab Sosial Perusahaan Dan Tata Kelola Perusahaan

The issue of tax avoidance remains intriguing for further investigation in empirical studies. This research was conducted to re-examine the influence of corporate social responsibility and corporate governance on aggressive practices in tax evasion. The data source is from manufacturing companies in the consumer goods industry sector listed on the Indonesia Stock Exchange between 2017 and 2021. This research used 168 companies with a purposive sampling method. Data analysis uses multiple linear regression using statistical software for social sciences. The research results show that the variables of corporate social responsibility, the presence of independent commissioners, and institutional ownership have a significant negative impact on aggressive practices in tax evasion. On the other hand, there is no significant influence of the audit quality variable on tax evasion. Therefore, the higher the level of corporate social responsibility disclosure, the proportion of the presence of an independent board of commissioners, the quality of audits, and the proportion of institutional ownership, the level of aggressive practices in tax evasion tends to decrease.

PFAS surveillance within a highly militarized island: a case study of Okinawa, Japan.

Per- and polyfluoroalkyl substances (PFAS) are a resilient class of anthropogenic contaminants of emerging concern with over 12 000 individual compounds that have been noted for industrial applications, consumer goods, and food packaging materials. In general, the most common contributors to PFAS environmental pollution are aviation facilities, specifically those that use aqueous film forming foams (e.g., at military bases and airports). In this study, we examined the presence of PFAS across Okinawa Island (Japan) due to its large-scale U.S. military presence throughout the island. Surface water was collected at 61 sites across the island to achieve maximum geographical coverage of the island while also collecting near suspected PFAS sources; 31 PFAS were monitored using a 12 min HPLC-MS/MS method. A total of 15 PFAS were detected and quantified around the island with a mean Σ15PFAS of 16.3 ng L-1 and a maximum site concentration of 164.3 ng L-1. Region-specific PFAS profiles were observed across the island, including the overwhelming presence of PFHpA in the northern region of the island, revealing the possibility of multiple PFAS source points in Okinawa. The resultant data herein provides the first island-wide examination of PFAS "hotspots" across Okinawa and is a critical first step toward increasing PFAS awareness and action.

Exploring DiPP (diisopentyl phthalate) neurotoxicity and the detoxification process in zebrafish larvae - A Silent contaminant?

Diisopentyl phthalate (DiPP) is present in many consumer goods, but can be absorbed into the human body, and can disrupt the endocrine system affecting reproductive health and fetal development. Studies revealed that biological samples of pregnant women in Brazil contained DiPP, raising even more the concerns about its usage. This study investigated how DiPP concentrations (12.5-1000μg l-1) affect the different developmental stages (24, 48, 72, 120, and 144 hpf) of embryos and larvae of zebrafish. DiPP induced deleterious alterations in neuromuscular development and morphometry of organs, Low concentrations of DiPP decreased acetylcholinesterase and cellular energy allocation concomitantly with increased glutathione S-transferase. Zebrafish swimming period seemed to be decreased not only due to direct neurotoxicity, but also to less allocation of energy for behavioral purposes. Moreover, high concentrations of DiPP induced spinal deformities and developmental alterations specially of the eye and liver of larvae. These findings emphasize that DiPP exerts complex effects that should be considered when assessing its potential effects on health of humans and the total environment. The biomarkers and behavioral parameters showed to be good complimentary early-warning tools exhibiting a high sensitivity compared to FET.