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Climate change-induced weather changes are severe and frequent, making it difficult to predict apparel sales. The primary goal of this study was to assess consumers' responses to winter apparel searches when external stimuli, such as weather, calendars and promotions arise and to develop a decision-making tool that allows apparel retailers to establish sales strategies according to external stimuli.

The theoretical framework of this study was the effect of external stimuli, such as calendar, promotion and weather, on seasonal apparel search in a consumer's decision-making process. Using weather observation data and Google Trends over the past 12 years, from 2008 to 2020, consumers' responses to external stimuli were analyzed using a classification and regression tree to gain consumer insights into the decision process. The relative importance of the factors in the model was determined, a tree model was developed and the model was tested.

Winter apparel searches increased when the average, maximum and minimum temperatures, windchill, and the previous day's windchill decreased. The month of the year varies depending on weather factors, and promotional sales events do not increase search activities for seasonal apparel. However, sales events during the higher-than-normal temperature season triggered search activity for seasonal apparel.

Consumer responses to external stimuli were analyzed through classification and regression trees to discover consumer insights into the decision-making process to improve stock management because climate change-induced weather changes are unpredictable.

Given the heated academic and policy debate regarding the fate of garment manufacturing in a high-wage developed economy in the 21st century, this study aims to explore the production and export strategies of apparel “Made in Ireland.”

A logistic regression analysis of 4,000 apparel items at the stock keeping unit (SKU) level sold in the market from January 2018 to December 2021 was conducted to evaluate the production and export strategy of apparel “Made in Ireland” versus foreign-made imported items sold in Ireland.

The statistical results showed that Ireland’s apparel manufacturing sector survived the market competition by leveraging non-price competing factors, such as distinct product assortment, cultural heritage, history and traditional craftsmanship.

The findings challenged the conclusions of the classic trade and economic development theories regarding the trajectory of the garment manufacturing sector and called for a rethink about the strategies for expanding garment manufacturing in a high-wage developed country in today’s global economy.

The paper explores the managerial perceptions in Indian apparel manufacturing firms related to production performance, challenges faced, causes of low efficiency and the government support needed.

A structured survey of Indian apparel manufacturing firms was undertaken in person and through the online mode; the questionnaire was designed to collect data on demographic profile of a firm using categorical questions and perceptions of its top managers using a five-point Likert scale.

The survey findings reveal that most apparel manufacturing firms believe that exporting promotes efficiency and adopt output orientation to production, which may not be suitable in a competitive and uncertain environment. Machines are not used much for value-addition and labour related issues are most pressing challenges. Government support is expected for several aspects such as power supply and skill development.

The paper is limited by the nature of the sampling method and sample size; perceptions should be explored without bias and with good judgement.

The survey findings suggest that government policy should have a firm-specific approach to support improved production performance along with generic policies to build infrastructure and logistical facilities.

To the best of authors’ knowledge, there has been no such exercise to study managerial perceptions related to production performance in Indian apparel manufacturing in the past decade.

The purpose of this study was to understand the impact of the coronavirus disease (COVID-19) pandemic on the global textile and apparel supply chain from the perspectives of industry professionals within the two leading production countries: Bangladesh and China.

Applying the theory of dynamic capabilities, a qualitative research design was employed using interviews with a total of 33 apparel industry practitioners, 15 in Bangladesh and 18 in China.

Findings indicate that four factors primarily impacted the extent to which COVID-19 disrupted a firm's supply chain: firm size, channel diversification, sourcing method and product type. Viewed through the lens of the theory of dynamic capabilities, findings point to the need for firms to address the challenges brought about by supply chain disruptions by creating opportunities.

It is important to understand the impact of COVID-19 in real time and within the two largest textile and apparel–producing countries globally, as they have borne much of the brunt of the supply chain disruptions brought on by COVID-19. This empirical study makes contributions to the apparel supply chain literature as it provides an in-depth investigation of what textile and apparel firms in China and Bangladesh have learned from the COVID-19 experience to better prepare for future unexpected global events.

This study aims to investigate the relationship between people’s socially and environmentally responsible apparel practices (SERAP) and valuing US made clothing, current perceptions of US made clothing and factors affecting apparel purchases.

An online survey was completed by 502 US consumer aged 18-65. Five factors were identified representing responsible apparel practices and US made clothing. Inter-factor correlations were tested. People’s perceptions toward US made clothing were examined through perceived quality, purchase experience and intentions to pay premium prices.

There was a positive correlation between SERAP and valuing US made clothing. Perceived quality of US apparel influenced both actual purchase and intentions to pay higher prices. Availability and affordability were major purchase factors.

US apparel companies that produce their products domestically may consider developing specific messaging that resonates with customers, taking advantage of the perception of high quality and being transparent with the cost of producing apparel domestically.

This study suggests domestically made apparel purchases as part of a move toward SERAP. Although previous studies have addressed consumer responsibility and sustainable businesses, the connection has been inconclusive. This study provides current data of renewed and growing interest in US made apparel and expands its value.

Textile and contemporary apparel manufacturers are adopting and integrating cutting-edge technologies to reduce their impact on the environment and gain an advantage in the marketplace. Most previous studies have ignored business intelligence systems (BIS), notably in the textile and apparel industry (T&A), in favor of looking at the larger picture of how big data would affect retail and distribution in a company. This is especially true for the T&As.

The authors report that they conducted 14 semi-structured interviews with 12 international luxury tourism service providers. In this case, researchers use snowball features and systematic techniques to select participants. A qualitative content analysis strategy is used to capture the focus of the interviews.

Problems with T&A company sustainability, opportunities to increase value creation via use of industry-leading business intelligence (BI) solutions and perceived roadblocks to BIS adoption were all found by the poll. Garment retail and distribution sector has benefited greatly from the increased use of Industry 4.0 technologies, especially those that provide better BI solutions. Determine the extent to which industry participation slows down or speeds up the process. The Company Information System (BIS) will help convince non-tech-savvy business owners of the financial, economic and environmental benefits of adopting certain technologies developed as part of the industry 4.0 movement.

The authors of this research claim theirs is one of the first to investigate what variables affect the uptake of BIS, ultimately hoping to find out how BIS may be used by T&A businesses to tackle environmental issues through the use of Industry 4.0 technologies. The purpose of this study was to see whether BIS might aid T&A firms with their sustainability issues.

In the last several years, there has been a meteoric rise in interest in big data and business analytics among firms and educational institutions alike. This paper tries to introduce readers to the concept of business analytics in a way that is both academic and accessible, considering both the present and future of the field. This paper begins with a quick introduction, followed by a summary of the three distinct forms of predictive modeling discussed.

In an effort to help aspiring analytics professionals, they have identified, categorized and evaluated the nine distinct players that are now active in the analytics market. Following this, they will provide a high-level summary of the many different research projects currently being worked on by their group.

This study aims to measure the competitiveness of top apparel exporting nations competing with China in different apparel product categories across the global environment.

Compound annual growth rate, trade competitiveness, market share percentages, revealed comparative advantage and its variant normalized revealed comparative advantage using two-, four- and six-digit harmonized system codes for the period of 2016–2021 were used to understand the comparative advantage of competing apparel exporting nations.

The findings revealed that China still holds a more decisive comparative advantage than its competitors over the majority of the product categories within the knitted or not knitted apparel and clothing accessories. The other competing nations hold better export competitiveness over China in specific categories. However, that is not sufficient to be the “Next China.”

The study has important implications for different stakeholders of the global apparel industry, such as governments, industry officials, policymakers, investors, researchers and students. The study’s limitations arise from using product categories as competitiveness indicators, notably relying on a macro level approach for measurement while the micro level perspective is not analyzed, which constitutes a significant limitation of the study.

This research thoroughly analyzes the competitive position of the top ten apparel-exporting countries in the global market.

The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

This study aims to propose and demonstrate a practical application of a new three-part holistic sensory evaluation (HSE) method for textiles and apparel based on the senses of sight, touch, hearing and smell. HSE method development was carefully documented, described and successfully applied to evaluate sensory characteristics and consumer perceptions and acceptance of bacterial cellulose (BC), a novel sustainable material for apparel.

In Part One of the HSE method, research participants described the material in their own words based on the senses of sight, touch, hearing and smell. In Part Two, they rated the intensities and their linking for 25 predetermined attributes describing BC. Part Three measured participants’ overall liking of BC and its perceived suitability for apparel and accessories.

Application of the HSE method resulted in an in-depth understanding of BC material. Areas for material improvements and positive characteristics were identified, providing direction for further development. Consumers found BC suitable for accessories and outer-layer garments but not for apparel.

Sensory evaluation of textiles and apparel has traditionally focused on the senses of touch and sight. The new HSE method allows evaluating the full range of sensory characteristics of materials/products and holistically assessing consumer perceptions. The method is especially useful for novel materials and wearable technology. BC has gained increased interests as a novel sustainable material, yet consumer studies have been lacking. This study reports a comprehensive evaluation of BC material from consumer perspective.

Businesses embark on cause-related marketing (CRM) initiatives as a marketing strategy to fortify consumers' behavioural intentions. Prior research indicates that human values could be tapped to understand the consumers' responses to perceived organizational motives behind undertaking social cause initiatives. This research employs Schwartz's theory of human values to examine consumers' patronage intentions towards CRM-linked fashion products. Moreover, fashion leaders play a crucial role in the diffusion of the latest fashion and fashion trends. This research investigates by integrating human values and fashion leadership, offering insights into CRM-linked fashion consumption motives.

The overarching goal was to investigate the complex interplay between human values and female fashion leadership to predict CRM patronage intention (CPI). Hence, a large-scale research study on 2,050 samples was undertaken by adopting threefold partial least squares–multigroup analysis–artificial neural network (PLS-MGA-ANN) to establish and empirically test a comprehensive model.

This study is unique as it establishes and validates the relative or normalized importance placed on human values by fashion leaders, thereby predicting CPIs. The results revealed that women with high-fashion leadership and specific value types (benevolence, universalism, self-direction) are more likely to patronize CRM-linked fashion retailers. In addition, the findings validated that women with low-fashion leadership and specific value types (tradition, security, conformity) are more likely to patronize CRM-linked fashion stores.

The findings provide a valuable rationale to non-profit marketers, fashion marketing experts and practitioners to design customer value-based profiling and manage crucial CRM decisions.