Footwear Industry Research Articles

Exploring the Mechanical and Thermal Impact of Natural Fillers on Thermoplastic Polyurethane and Styrene–Butadiene Rubber Footwear Sole Materials

The increasing concern for sustainability in the footwear industry has spurred the exploration of eco-friendly alternatives for materials commonly used in sole manufacturing. This study examined the effect of incorporating rice straw and cellulose as fillers into soles made from either styrene–butadiene rubber (SBR) or thermoplastic polyurethane (TPU). Both fillers were used as a substitute in mass percentages ranging from 5 to 20% in the original SBR and TPU formulas, and their impact on mechanical properties such as abrasion and tear resistance, as well as thermal properties, was thoroughly evaluated. The results demonstrated that the inclusion of fillers affects the overall performance of the soles, with the optimal balance of mechanical and thermal properties observed at a 10% filler content. At this level, improvements in durability were achieved without significantly compromising flexibility or abrasion resistance. Thermal analysis revealed increased thermal stability at moderate filler contents. This research not only offers a sustainable alternative to traditional materials but also enhances sole performance by improving the composition. Furthermore, this study paves the way for future research on the feasibility of incorporating eco-friendly materials into other consumer product applications, highlighting a commitment to innovation and sustainability in product design.

Studying the Moderating Effects of Additive Manufacturing Best Practices Between Supply Chain Complexity and Its Performance

Background: Supply chain performance (SCP) is impacted by complexity brought about by static and dynamic drivers. This study aims to investigate the effects of supply chain complexity (SCC) on SCP and ascertain whether additive manufacturing best practices have moderating effects on this relationship. Methods: Using data from 29 Ethiopian footwear industries and 205 respondents, the relationship established in the theoretical framework was validated using structural equation modelling (SEM). Results: The study’s findings provided several important insights. First, upstream supply chain complexity (USSCC), midstream supply chain complexity (MSSCC), and downstream supply chain complexity (DSSCC) negatively affect SCP. Second, additive manufacturing best practices have significant moderation effects between supply chain complexity and supply chain performance. Third, the negative impacts of USSCC and MSSCC on SCP are reduced at a higher level of additive manufacturing adaptation. The findings of this study also revealed that the effects of DSSCC on SCP have no difference at both low and high levels of additive manufacturing best practices. Conclusions: This work offers the first empirical investigation to which the detrimental effects of SCC on SCP are mitigated or improved through the moderating role of additive manufacturing best practice.

The role of big data analytics in the footwear supply chains: a multiple case study perspective

Purpose This paper aims to analyze the importance of big data analytics (BDA) and supply chain analytics for sustainable supply chain management in all types of enterprises in the footwear industry. The importance and implementation of BDA in supply chain management have been discussed in this research paper, and a conceptual framework is proposed for the implementation. Design/methodology/approach The previous research indicates that the application of BDA and supply chain analytics is the key point to establishing sustainable supply chain management. Even though there are several types of research on the implications of BDA, there is still a gap in practical implications in organizations. For a better understanding, comparison of frameworks has been done for literature support. Further, 11 in-depth, semi-structured interviews have been conducted with four organizations from the footwear industry, and a conceptual framework has been proposed. Findings This research demonstrates an important gap in the literature through a thorough investigation of how firms can improve operational efficiency and productivity through the framework application and whether it is feasible to apply this within the global footwear industry or not. In conclusion, the research has denoted that despite lack of understanding related to sustainability agendas and not having proper ERP or BDA systems, the organizations operating in Pakistan still met some standards of sustainability and are moving toward achieving more. Research limitations/implications The research has pointed out the importance of the integration of all stakeholders in the supply chain through a proposed framework that aligns and guides the stakeholders so that the policies and other constraints may be taken into consideration while revising sustainable supply chain strategies. Practical implications This study will help increase sustainability through the application of BDA technology, which will benefit various stakeholders, particularly those in the footwear industry. Originality/value This study has proposed a framework based on three stages of the implementation of BDA in the existing supply chain to maintain and achieve sustainability in the organization in the footwear industry. This three-stage framework covers many aspects that were not covered in the literature before.

Research on the Predictive Ability of Economic Policy Uncertainty on Stock Returns of Industries

In recent years, the emergence of economic policy uncertainty has had a certain impact on stock returns. It can be used as a research object to explore whether economic policy uncertainty can significantly predict future stock returns. This paper studies the predictive ability of economic policy uncertainty based on relevant data from major industries in the United States from January 1985 to December 2023, including Food industry (Food), Retail Stores industry (Rtail), Fabricated Products industry (FabPr), Drugs, Soap, Perfumes, Tobacco industry (Cnsum), Construction and Construction Materials industry (Cnstr), Consumer Durables industry (Durbl), Automobiles industry (Cars), Textiles, Apparel & Footwear industry (Clths), Machinery and Business Equipment industry (Machn), Chemicals industry (Chems), and Transportation industry(Trans), Utilities industry (Utils), Steel Works Etc industry (Steel), Mining and Minerals industry(Mines), Oil and Petroleum Products industry (Oil), and Banks, Insurance Companies, and Other Financials industry (Finan). Through both in-sample and out-of-sample examines, it is found that economic policy uncertainty is a reliable indicator for predicting stock returns, and its predictive performance is better in Food industry, Retail Stores industry, Fabricated Products industry, Transportation industry, Construction and Construction Materials industry, Consumer Durables industry, Automobiles industry, Textiles, Apparel & Footwear industry, Machinery and Business Equipment industry, Chemicals industry, and Drugs, Soap, Perfumes, Tobacco industry than in Utilities industry, Steel Works Etc industry, Mining and Minerals industry, Oil and Petroleum Products industry, and Banks, Insurance Companies, and Other Financials industry. Meanwhile, by replacing the measurement indicator of economic policy uncertainty, conducting long-horizon forecasting, and using different evaluation periods for robustness checks, it is found that the research conclusions are robust.

A Comparative Study of Different Unorganized Sectors’ Workers in India to Identify Musculoskeletal Disorder Prevalence through Empirical Survey and Deep Learning Methods

Background:: Musculoskeletal disorders (MSDs) are a group of non-fatal injuries that can occur as a result of various repetitive workplace activities, mainly in unorganized sectors. Workers who engage in highly repetitive activities involving constant hand effort, localized mechanical pressure, and vibration are more prone to developing these disorders. Objective:: The objective of this research was to determine the prevalence of MSDs among workers in various unorganized sectors in India who perform hand-intensive occupations. Method:: A cross-sectional study was conducted, involving 340 workers from diverse groups such as sugarcane farmers, footwear industry workers, and tarpaulin weavers, to accomplish this goal. Data for the survey was collected using a questionnaire. Additionally, a comprehensive time study and a deep learning-based posture detection study were conducted on the different activities performed during the workers' occupational tasks. The chi-square test was used to assess the relationship between discomfort and work repetitiveness. Result:: The data analysis revealed that the working activities (especially cutting/harvesting, rubber cutting, etc.) of unorganized sector workers were repetitive, with more than half of each activity’s work cycle involving a similar usage pattern. Furthermore, a significant association was observed between the level of discomfort and work repetitiveness among workers in different sectors (sugarcane farmers: p < 0.01, footwear industry workers: p < 0.05, tarpaulin weavers: p < 0.05). Consequently, it can be concluded that prolonged occupational activities involving repetitive and prolonged standing may contribute to the occurrence of MSDs. Conclusion:: Ergonomic interventions/modifications in the form of patent work will be necessary to prevent these issues in the near future.

IMPROVING THE CIRCULAR ECONOMY IN THE FOOTWEAR INDUSTRY

The article presents a circular economy proposal as a way to promote greater sustainability in the footwear industry. As part of the work, we analysed the essential components for a shoe and the materials used in the production of footwear. Currently, new proposals have emerged for footwear that use materials derived from waste and the forwarding of specific end-of-life products. These new concepts are associated with added value and targeted marketing towards sectors of society more concerned with the industry's environmental impact. This reinforces the interest in the positioning of the footwear industry in relation to the circular economy. The purpose of this article focuses on the last phase of the circular economy – recycling, educating, and valuing the role of the consumer through the collection, treatment and forwarding of used footwear materials with the aim of reducing waste in landfills but simultaneously increasing awareness of the footwear industry.

Evaluation of the Performance of Neural and Non-Neural Methods to Classify the Severity of Work Accidents Occurring in the Footwear Industry Complex

In the footwear industry, occupational risks are significant, and work accidents are frequent. Professionals in the field prepare documents and reports about these accidents, but the need for more time and resources limits learning based on past incidents. Machine learning (ML) and deep learning (DL) methods have been applied to analyze data from these documents, identifying accident patterns and classifying the damage’s severity. However, evaluating the performance of these methods in different economic sectors is crucial. This study examined neural and non-neural methods for classifying the severity of workplace accidents in the footwear industry complex. The random forest (RF) and extreme gradient boosting (XGBoost) methods were the most effective non-neural methods. The neural methods 1D convolutional neural networks (1D-CNN) and bidirectional long short-term memory (Bi-LSTM) showed superior performance, with parameters above 98% and 99%, respectively, although with a longer training time. It is concluded that using these methods is viable for classifying accidents in the footwear industry. The methods can classify new accidents and simulate scenarios, demonstrating their adaptability and reliability in different economic sectors for accident prevention.

Circular economy strategies: a fuzzy DEMATEL decision framework for the fast fashion footwear manufacture

The fast fashion industry significantly impedes sustainability by its rapid production cycles, low-cost products, and heavy carbon footprint. Nowadays, circular economy (CE) has become an interesting concept, which follows the “take-make-dispose” model and allows products, materials, and resources to be in use as long as possible. There is a paucity of research in the identification of circular economy strategies (CES) and mapping them based on their interrelationships, which is very important from a managerial perspective. In this vein, this study identifies nine CES and analyzes their causal relationships using the Fuzzy Decision-Making Trial and Evaluation Laboratory method in the context of fast fashion footwear manufacture. The key contributions include providing actionable insights for implementing CE practices, enhancing the sustainability of the footwear industry, and offering a strategic roadmap for industry stakeholders. The results and implications of this study will guide footwear industry decision-makers in making a strategic map considering the cause-and-effect interrelationships among the CES for implementing CE business practices in the footwear industry.

Simulation model to analyze the impact of work on absenteeism

AbstractShoe manufacturing companies often use overtime work but neglect the impacts and importance of physical recovery time. Ergonomic methods aim to analyze this, but they focus on deterministic aspects, which limits their ability to evaluate working conditions amid variations over time. This research explores how a simulation model can mitigate these limitations and enhance analysis of overtime and physical recovery on worker absenteeism. The objective was developed a simulation model using System Dynamics (SD) to represent working conditions and assess the influence of overtime and recovery time in Brazil's footwear industry. An Ergonomic Analysis of Work was conducted in a large company's production cell. Using SD, were constructed a causal and simulation model to analyze three scenarios. An additional hour of work increased physical overload by 44%, leading to 5, 4 leave requests, and 48 days of absenteeism per year. Increasing recovery time by 15 min reduced overload to 38,96%, resulting in 4, 9 leave requests and 13,68 days of absenteeism. The SD simulation model mitigated the limitations of ergonomic methods in understanding the dynamic relationships over time, emphasizing the importance of actively managing overtime and physical recovery time.

Rebooting Bata: The challenges of repositioning a heritage brand

Founded as a family-owned business in 1894, Bata Corp. has grown to become a major player in the footwear sector, with a presence in more than 70 countries. In India, the company established itself as the primary producer of affordable, durable footwear, with the result that the majority of generation X and millennial consumers remember growing up with Bata shoes, having worn them in their school days and often into early adulthood. Unfortunately, childhood memories can be difficult to translate into glamour; as a result, Bata struggled to position itself as a fashionable modern brand. This case study delves deep into the nuances of repositioning a heritage brand, and explores how Bata eventually succeeded in repositioning itself as a premium contemporary brand. The paper highlights the challenges associated with balancing legacy brand associations with desired image. It also shares valuable insights regarding the evolution of India’s fashion and footwear industry, changing consumer behaviour in emerging markets, and the increasing globalisation and democratisation of fashion.

Deep Learning based Counterfeit Nike Shoes Detection using YOLOv8 for Object Detection

The fashion and footwear industries, where brand value and customer trust are paramount, are under constant threat from counterfeit products. This research presents a deep learning-based solution for detecting counterfeit Nike shoes using the YOLOv8 model for object detection. the dataset included four classes: “Nike Fake Air Force,” “Nike Fake Jordan 1,” “Nike Original Air Force,” and “Nike Original Jordan 1,” comprising a total of 3,860 images. These were split into training (70%), validation (20%), and testing (10%) sets. The pre-trained, medium-sized YOLOv8 model was used for detection and classification, yielding promising results. The model achieved a mAP of 95.0%, with precision and recall scores of 92.2% and 91.8%, respectively, on the validation set. The images were web scrapped with the Chrome extension called "Download All Images" and then manually filtered so that they would be relevant and of good quality. Each image was then manually labelled using the RoboFlow platform. Nevertheless, the model appears to be promising for implementation in combating counterfeit products, with a high potential accuracy and efficiency.

Evaluating the sources of microplastic contamination and quantifying its abundance in the Balu River, Dhaka, Bangladesh.

Microplastics (MPs) are prevalent environmental pollutants due to their durable composition, extensive use, and improper disposal. Despite their widespread presence, rivers have received less attention in microplastic research than other water bodies. This study focused on investigating the origins, prevalence, spatial distribution, and physicochemical characteristics of microplastics in the surface waters of the Balu River, located in Dhaka, Bangladesh. Surface water samples were collected at six sampling sites of Balu River (each about 1-5km apart) adjacent to the footwear industry, jute factory, textile mill, paper mill, agro and beverage factory, and cement plant. The study found that the average concentration of microplastics in the sampled water bodies was 102.5 ± 12.83 (items/l). Samples near the textile mill had the highest microplastic abundance (122 ± 18 items/l), while the cement plant had the lowest (58.5 ± 8 items/l). Analysis using a stereomicroscope revealed that fibers (29%), microplastics smaller than 100µm (45%), and transparent microplastics (19%) were the most prevalent types observed in terms of shape, size, and color, respectively. Furthermore, scanning electron microscopy (SEM) observation suggested the potential for additional degradation of these microplastics into smaller particles, potentially reaching the nanoplastic scale. Additionally, Fourier transform infrared (FTIR) analysis identified 07 distinct polymer types among the microplastics: nylon (24%), polyvinyl chloride (19%), high-density polyethylene (17%), low-density polyethylene (14%), polystyrene (12%), polypropylene (7%), and nitrile (7%). The findings of this study serve as a crucial indicator of microplastic contamination, providing valuable insights into the sources and magnitude of microplastic pollution within the significant freshwater ecosystem of Balu River, Bangladesh, particularly focusing on its river systems.

Country‐level analysis of the relationships between sustainability and the textile–clothing–leather–footwear industries

Country‐level analysis of the relationships between sustainability and the textile–clothing–leather–footwear industries

Impact of Satisfaction on Customer Loyalty: Perspectives from the Footwear Industry in Peru

Impact of Satisfaction on Customer Loyalty: Perspectives from the Footwear Industry in Peru

Dye Removal From Tannery Wastewater Utilizing Footwear Waste: A Sustainable Approach

ABSTRACTWaste‐to‐3R (reduce, reuse, and recycle) is a promising mass balance approach in the leather sector for addressing the current challenge of overproduction of rubber sole waste in the footwear industry and dye pollution in tanneries. In this study, low‐cost charcoal derived from discarded natural rubber (NR) soles was effectively employed to remove anionic and cationic dyes from a model tannery dye solution, aligning with mass balance approaches in the leather sector. Discarded rubber charcoal (DRC) was prepared at 350°C using a self‐fabricated pyrolytic cell. The resulting charcoal was then dried, ground, and separated through 40‐mesh size lab‐scale sieves, and it was subsequently employed for the removal of dyes from tannery wastewater. The dye removal performance was optimized by adjusting parameters such as dosage, pH, contact time, and concentration. The maximum adsorption capacity and removal efficiency of the anionic acid dye (AD) were found to be 158.22 mg/g and 88.39% at pH 1, respectively, while those of the cationic methylene blue dye were 166.18 mg/g and 85.53% at pH 12, respectively, between 15 and 30 min, depending on the DRC conditions. Fresh charcoal and dye‐loaded charcoal were characterized through Fourier transform infrared spectroscopy, x‐ray diffraction, Brunauer–Emmett–Teller, scanning electron microscope (SEM), and transmission electron microscope with Energy‐Dispersive X‐ray (EDX) Spectroscopy for respective functional groups and morphology studies, and zeta potential measurements were employed to characterize the charcoal surface charge. The SEM image revealed that the shape of the DRC particles resembles a honeycomb structure, with an average size of 573.56 µm. The adsorption kinetic study indicates that the Freundlich isotherm model and pseudo‐second‐order kinetics were well‐fitted for dye removal in this study. The charcoal exhibited robust stability, retaining its capacity of 57.42 mg/g of AD and 44.94 mg/g of MB dye after four reuse cycles. This resilience was observed in treatment with various desorption agents, including HCl, CH3COOH, NaOH, and C2H5OH. The findings of this study suggest that NR‐derived charcoal could be used as a successful substitute for commercial activated carbon in wastewater treatment to get rid of the acid and basic dyes of the leather industry. Based on the observed results, a plausible mechanism was also proposed.

Source Profiles and Impact of Volatile Organic Compounds in Typical Industries in Luohe City

Ten typical industries in Luohe City were selected for the sampling of organized emissions of volatile organic compounds （VOCs）, and 114 VOCs components of each sample were detected to analyze their source characteristics and effects. The results showed that VOCs emissions of packaging and printing were mainly composed of OVOC （60.9%）. In terms of the industrial coating, aromatic hydrocarbons （42.4%） and OVOC （38.9%） were the main VOCs species. The emissions of the footwear, furniture manufacturing, and paper industries were mainly composed of OVOC （32.3% - 42.6%） and aromatic hydrocarbons （20.7% - 33.7%）, with noticeable halogenated hydrocarbons. Chemical and pharmaceutical industries mainly emitted halogenated hydrocarbons, with the proportions of 59.3% and 46.6%, respectively. The emissions of the brick industry were primarily composed of alkane （62.7%）, and OVOC （48.5%）, and halogenated hydrocarbons （19.7%） were the main contributors to VOCs emissions of the thermal industry. OVOC （48.1%） and alkane （29.4%） were the dominant species for the food manufacturing industry. In the packaging and printing industry, acetone （14.8%）, isopropanol （14.0%）, ethylacetate （11.1%）, and toluene （10.2%） were the characteristic VOCs species. The emissions of industrial coating were dominated by isopropanol （25.6%）, toluene （15.0%）, m/p-xylene （12.4%）, and acetone （7.1%）. In the furniture manufacturing industry, m/p-xylene （15.8%）, followed by hexanal （15.1%）, 1,2-dichloroethane （9.6%）, and acetone （8.4%） were the characteristic VOCs species. The emissions of the footwear industry were dominated by acetone （18.9%）, toluene （18.1%）, methylene chloride （8.0%）, and acetaldehyde （6.8%）. The characteristic species of the chemical industry were methylene chloride （23.9%）, 1,2-dichloroethane （14.7%）, acetone （12.7%）, and trichloromethane （11.1%）, and those for the pharmaceutical industry were bromoethane （36.7%）, acetone （19.2%）, benzene （5.0%）, and vinyl acetate （3.0%）. The emissions of the brick industry were mainly ethane, propane, ethylene, and benzene. Acetone, toluene, acetylene, and acetaldehyde were the primary VOCs species in the paper industry. The emissions of the food manufacturing industry were dominated by acetaldehyde, n-pentane, acrolein, and n-heptane. The emissions of the thermal industry were characterized by acetone, acetaldehyde , benzene, and toluene. Although different industries emitted various characteristic VOCs species, in general, acetone, isopropanol, benzene, toluene, m/p-xylene, ethane, acetaldehyde, and methylene chloride were the main characteristic species in most industries in Luohe. OVOC and aromatic hydrocarbons had higher contributions to ozone generation potential （OFP）, and aromatic hydrocarbons contributed over 80.0% to secondary organic aerosol formation potential （SOAP）. The source reactivity of ozone [SR（O3）] of the food and furniture manufacturing industries were higher, with values of 3.7 g·g-1 and 3.5 g·g-1, respectively, whereas the source reactivity of secondary organic aerosol SR（SOA） of the industrial coating, furniture manufacturing, and footwear industries were higher, with the values of 0.021, 0.017, and 0.014 g·g-1. Hence, the food manufacturing, industrial coating, and furniture manufacturing industries should be the primary industries for the collaborative control of PM2.5 and ozone in Luohe City, of which the furniture manufacturing industry was the top priority.

Influence of extended working hours and physical recovery on absenteeism in the footwear industry from a system dynamics model

Objectives. Work-related musculoskeletal disorders (WMSDs) are recurrent in the footwear industry, resulting in absenteeism. This study aimed to quantitatively analyze the influence of overtime work and physical recovery time on the occurrence of WMSD-related absenteeism using a system dynamics model. As ergonomic methods have limitations in quantitatively simulating the behavior of these relationships, the integration of computational modeling techniques has emerged as a methodological alternative to bridge this gap. Methods. An ergonomic work analysis (EWA) was developed in a production cell of a large company. A model of causal relationships (causal loop diagram) and a simulation model (flow and stock diagram) were then developed, where three scenarios for overtime and physical recovery time were analyzed. Results. Working an additional hour resulted in a 42% increase in physical overload, leading to 7.62 leave requests per year and 78.7 days of employee absenteeism. Increasing the physical recovery time by 15 min reduced the overload to 36.5%, resulting in 6.8 leave requests per year and 71.1 days of employee absenteeism. Conclusions. Properly managing excess workload and providing adequate physical recovery for professionals is necessary to mitigate the productivity impacts of absenteeism in the footwear industry.

Comparative Study of the Foaming Behavior of Ethylene-Vinyl Acetate Copolymer Foams Fabricated Using Chemical and Physical Foaming Processes.

Ethylene-vinyl acetate copolymer (EVA), a crucial elastomeric resin, finds extensive application in the footwear industry. Conventional chemical foaming agents, including azodicarbonamide and 4,4'-oxybis(benzenesulfonyl hydrazide), have been identified as environmentally problematic. Hence, this study explores the potential of physical foaming of EVA using supercritical nitrogen as a sustainable alternative, garnering considerable interest in both academia and industry. The EVA formulations and processing parameters were optimized and EVA foams with densities between 0.15 and 0.25 g/cm3 were produced. Key findings demonstrate that physical foaming not only reduces environmental impact but also enhances product quality by a uniform cell structure with small cell size (50-100 μm), a wide foaming temperature window (120-180 °C), and lower energy consumption. The research further elucidates the mechanisms of cell nucleation and growth within the crosslinked EVA network, highlighting the critical role of blowing agent dispersion and localized crosslinking around nucleated cells in defining the foam's cellular morphology. These findings offer valuable insights for producing EVA foams with a more controllable cellular structure, utilizing physical foaming techniques.

Development and Application of a Lignin-Based Polyol for Sustainable Reactive Polyurethane Adhesives Synthesis.

In response to the environmental impacts of conventional polyurethane adhesives derived from fossil fuels, this study introduces a sustainable alternative utilizing lignin-based polyols extracted from rice straw through a process developed at INESCOP. This research explores the partial substitution of traditional polyols with lignin-based equivalents in the synthesis of reactive hot melt polyurethane adhesives (HMPUR) for the footwear industry. The performance of these eco-friendly adhesives was rigorously assessed through Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), rheological analysis, and T-peel tests to ensure their compliance with relevant industry standards. Preliminary results demonstrate that lignin-based polyols can effectively replace a significant portion of fossil-derived polyols, maintaining essential adhesive properties and marking a significant step towards more sustainable adhesive solutions. This study not only highlights the potential of lignin in the realm of sustainable adhesive production but also emphasises the valorisation of agricultural by-products, thus aligning with the principles of green chemistry and sustainability objectives in the polymer industry.

The Development of Operation Management in Industrial Enterprises Under Digital Transformation-Taking the Footwear Industry as An Example

The Development of Operation Management in Industrial Enterprises Under Digital Transformation-Taking the Footwear Industry as An Example