传统手工艺（开了35年的裁缝店）小微企业Z公司的运营转型研究

The significance of this topic arises from the rapid expansion of digital technologies, changing consumer preferences, and the need for companies to adapt to today's market dynamics. Tailoring products and services is essential for businesses to maintain their competitive edge. Digital transformation is a key trend in today's business environment. It affects every aspect of a company, from internal operations to how products are conceived. Employing innovative technologies such as artificial intelligence (AI) and Big Data allows businesses to enhance performance and deliver personalized offerings that cater to individual consumer demands. These tools facilitate better demand forecasting, analysis of customer actions, and increased supply chain effectiveness. This research aims to explore how artificial intelligence and big data impact the digital shift in commodity policy. Specifically, it will investigate how these technologies assist in creating customized products that satisfy contemporary consumers, and how their application can reshape strategies for product development and marketing.This piece explores the theoretical principles underlying digital transformation in product policy. Special emphasis is placed on understanding product policy and adjusting it to digital advancements. The text also investigates how big data contributes to crafting personalized products. It focuses on incorporating big data into the process of creating tailored products. The part that AI and big data play in personalization overall is outlined. It assesses the possibilities and progress of digital transformation within commodity policy, specifically concerning trend prediction through AI and big data. The results regarding the digital transformation of commodity policy are provided, emphasizing how AI and big data influence the development of custom products, which provides significant practical benefits for businesses wanting to align their strategies with the current market and enhance customer relations.

Purpose The purpose of this study is to introduce a framework aimed at helping manufacturing companies in developing countries start their digital transformation journey, focusing on small and medium manufacturers. Design/methodology/approach This study proposes a CAP-Do cycle framework to facilitate digital transformation at the shop floor level. This study emphasises effective data collection using affordable Internet of Things tools and sensor statuses to differentiate between machine and human losses in semi-automated production lines. This paper also compares unit- and time-based overall equipment effectiveness indicators for measurement and offers a step-by-step analysis guide. Findings Sensor data’s active and inactive statuses help identify whether losses stem from machine or human issues, crucial for semi-automated production lines in developing countries. Accurate loss data guide improvements in machinery and operator activities. Additionally, time-based calculations of performance and quality rates provide a detailed loss breakdown, unlike unit-based methods that overlook process time variations. Research limitations/implications The framework’s implementation is tested on a prototype testbed, suggesting its real-world application may require adjustments to address the diverse factors of loss encountered in actual production environments. Originality/value This study outlines methods for data collection and detailed analysis using external sensors to classify machine and human issues. This study advocates for applying time-based overall equipment effectiveness calculations within the CAP-Do cycle for continuous improvement.

Recent advancements in digital technologies have significantly impacted our daily lives and many organizations’ operations. Digitalization is influencing the way how we work, shop, travel, and communicate. In organizations, digital transformation (DT) leverages data to enhance operational performance and customer experiences, requiring strategic and organizational changes in culture, processes, and infrastructure. This complexity makes DT a critical puzzle for maintaining competitiveness. Understanding digital platforms, emerging technologies, and trends—collectively known as digital innovation—is crucial in successful DT strategies. Regardless of the type of digital strategy chosen, a DT initiative generally involves three key steps: evaluating current company purposes and processes, understanding market needs, and leveraging data for innovation to predict future customer needs. Indeed, in the era of machine learning and artificial intelligence (AI), data is vital for creating values and improving digital solutions, impacting both internal and external stakeholders. As companies navigate a smarter, connected world, they must redefine strategies, impacting every step of their traditional value chain. As such, digital technologies are driving societal and industrial disruptions, fostering new business models through innovations, such as Internet of Things, cloud computing, big data analytics, and AI. In the current fourth industrial revolution, also known as Industry 4.0, despite the challenges, from organizational and cultural change, through cybersecurity, to data privacy and workforce displacement, digital tools offer opportunities to transform user experience, operational processes, and business models so that companies can remain competitive in a rapidly evolving digital landscape.

Digital transformation has brought significant changes to the local trade ecosystem in Indonesia, including Bone Regency. This study aims to explore the readiness of MSME sellers and consumer perceptions of empowerment features in e-commerce platforms, using a phenomenological qualitative approach. A total of 10 sellers and 10 consumers who are active on the Shopee, Tokopedia, and TikTok Shop platforms were interviewed in depth, supported by virtual observation and document analysis. The results of the study indicate that the digital readiness of sellers is influenced not only by the availability of devices and networks but also by digital literacy, innovative promotional strategies, self-learning, and support from family and community. Sellers who can adapt creatively and actively across platforms are more likely to thrive in the competitive digital market. On the consumer side, features such as promotions, free shipping, ratings, reviews, and ease of returns are key factors in empowering and building trust. A preference for local products also grows stronger when supported by a good digital reputation and responsive customer service. However, there are challenges in the form of unequal access to digital training and the need for platform policy innovations that are more friendly to local MSMEs. This study emphasizes the importance of strengthening digital literacy, cross-actor collaboration, and inclusive strategies to ensure that digital transformation is effective, inclusive, and sustainable at the local level.

MSMEs, which stands for Micro, Small, Medium Enterprises, have a number of problems, including the lack of use of technology in business development and obstacles in accessing market information. Digital transformation allows MSMEs to utilize technology in developing their businesses, increasing operational efficiency and better accessing market information. This research aims to utilize digital transformation in entrepreneurship in the digital era and its application in the business development of Toko Madi. This research uses a mobile application development approach to create a digital platform for MSMEs "Toko Madi." This application includes a login page, profile settings, item catalog, purchase history, and management features for shop owners, such as stock management, shipping, and sales data. It is hoped that the results of this research can increase the income of "Toko Madi" MSMEs by enabling them to reach customers outside the city and take advantage of the benefits of digital transformation. This digital transformation includes the process of digitizing the business, utilizing mobile applications, and using analytical tools to increase efficiency, productivity, and innovation. In conclusion, digital transformation is an important step for MSMEs in facing challenges and competing in an increasingly competitive global market. With this mobile application, MSMEs can increase their online presence, manage their business better, and adapt to dynamic changes in the digital era.

In today's rapidly evolving business landscape, the significance of digital transformation for Small and Medium-sized Enterprises (SMEs) cannot be overstated. CV Karya Makmur, an Indonesian automotive repair shop, stands at the forefront of this change, recognizing the urgent need to incorporate advanced Information and Communication Technologies (ICTs) into its operations. This transformation is not just about adopting new technologies; it is a comprehensive shift that redefines how the business interacts with customers, optimizes operational processes and improves its overall financial health. The journey of CV Karya Makmur highlights the broader implications of digital transformation in this sector. This case study delves into the multifaceted process of integrating technologies such as augmented reality (AR) and artificial intelligence (AI) to enhance service efficiency, tackle logistical hurdles, and improve access to vital information. Yet, the transition from conventional practices to a digital framework is fraught with obstacles, primarily due to resistance to change. Effective change management, focusing on the human elements of organizational transformation and employee engagement, is pivotal. CV Karya Makmur's experience underscores the critical need for digital systems that promote data-driven decisions, standardize operations, and facilitate better communication. Despite the initial challenges, the potential benefits—increased productivity, reduced operational costs, and a competitive edge in the market—are compelling. This study suggests that considering an organization's unique context and objectives, a tailored digital transformation strategy is essential for leveraging technology to enhance business outcomes in developing countries like Indonesia.

The automotive service industry has significantly transformed in the last decade, mainly by introducing new technology, altered consumer demands, and the necessity of heightening or scaling down operations. Small, independently owned local workshops have long characterized the industry, but how value is created, delivered, and captured is now experiencing a significant change. This study examines the business model discussion of the automobile service industry concerning transforming local stores into national scalable and distinctive brands that can extend to greater regions. A qualitative multiple-case study was used to analyze three car service companies in sub-Saharan Africa that have grown known brands out of their small businesses. The interviews, financial documents, and customer feedback were used as the sources of information, which were analyzed using Business Model Canvas and SWOT framework. The results show that digital integration, the standardization of the processes, the model of franchising, and the relationship with customer-centered innovations may become the drivers of scalability. Nevertheless, issues like scarcity of resources, skills shortages, and stable service quality levels at each service point remain. The research adds to the literature on service business innovation, providing valuable experience to aspiring, budding entrepreneurs, investors, and policymakers to innovate their car service business or diversify given modernization. It establishes that transformation is not a standard procedure but requires a strategic fit to market situations, technological preparedness, and customer requirements. This paper also discusses The usefulness of branding strategies in line with operational practices to achieve sustainability and expand the ever-changing automotive service environment.

This study aims to examine the impact of implementing the Quick Response Code Indonesian Standard (QRIS) in supporting digital transformation among micro, small, and medium enterprises (MSMEs), with a case study at Toko Mikha Shop in Palu City. The research employed a qualitative approach through in-depth interviews, observations, and document analysis, complemented by descriptive quantitative data. The findings reveal a significant shift in transaction patterns after the adoption of QRIS, where digital payments accounted for 50% of total transactions, compared to previously 100% cash payments. Furthermore, the shop’s monthly sales turnover increased by 20%, rising from IDR 15,000,000 to IDR 18,000,000. QRIS was found to simplify payment processes, accelerate transactions, enhance operational efficiency, and support more accurate and organized financial record-keeping. Its implementation also contributed to improved customer satisfaction. However, challenges such as a 0.7% transaction administration fee, delays in fund disbursement, and unstable internet connectivity remain critical issues. This study recommends enhancing digital literacy among MSME actors, improving technological infrastructure, and providing supportive policies to optimize the sustainable use of QRIS

In the digital era, traditional industries confront an existential choice: fundamentally modernize or become irrelevant. This study demonstrates that sustained change requires not just the adoption of new technology but also the strategic coordination of three interrelated dynamic capacities. Through an in-depth analysis across sectors like automotive manufacturing, retail logistics, and utility operations—industries challenged by outdated systems and cultural inertia—the study demonstrate that lasting renewal requires: 1) perceptual acuity to detect emerging threats and opportunities within market complexity, 2) decisive agility to act quickly by mobilizing resources and experimenting, and 3) transformational courage to reconfigure cultural foundations and infrastructure. Importantly, it shows how mismatched skills generate vulnerability: enhanced sensing without action causes “paralysis by analysis” (e.g., merchants’ understanding of environmental trends but lacking procurement agility), while reconfiguration without strategic sensing results in aimless disruption. The results suggest that integrating capacity development breaks down deep-rooted obstacles like technical lock-in and identity-based reluctance, as shown by manufacturers bringing together shop-floor veterans and data scientists to co-create AI solutions. The study provides practitioners with realistic frameworks for implementing weak-signal detection systems, creating CEO-supported innovation “sandboxes,” and fostering psychological safety to allow worker reskilling. For researchers, reconfiguration is redefined as a cultural transformation, and ambidextrous governance addresses the stability-agility conundrum. Finally, this triad of talents strengthens digital resilience—the organization’s capacity to transform continual disruption into a persistent competitive advantage. The road from fragility to vitality begins with capacity orchestration, not technology.

Abstract Tea shops are also one of the busiest and commonly used small-scale businesses, especially in India and many countries in Asia. Even though there are many tea shops that serve several people every day, many of them are using manual procedures for ordering, billing, and handling the demands of the customers. These manual procedures usually cause delay, error occurrence, poor customization, and difficulty in handling customer orders, especially during busy times. By the rapid advancements in smartphone technology and the internet, people are expecting faster and more convenient services, thereby resulting in the need to modernize the tea shop. This paper aims to introduce a smarter web & mobile-based tea shop management system to transform the traditional tea shop into a digital service facility. Customers will be able to view the categorized digital menu, customize their preferences, place orders beforehand, and monitor the status of their orders in a very short time using this new system, in addition to many other features such as artificial intelligence in dealing with customer demands. From the business perspective, the system provides the tools for management in menu items, order processing, reservation handling, and customer information storage. The proposed solution improves service efficiency, reduces manual errors, and enhances customer satisfaction, at the same time providing a practical, affordable, digital platform that suits modern tea shop environments. Keywords Tea shop automation, Web application, Mobile application, Digital menu, Order management, AI recommendation, Voice assistant

Nou Coffee is a local coffee shop in Medan adopts a modern, fast, efficient, and digitally integrated concept to deliver high-quality coffee. However, consumer loyalty has recently declined, indicated by fewer repeat visits and reduced digital interactions. The implementation of Customer Relationship Management (CRM) has often been less effective due to its generalized interactions, highlighting the need for more personalized, data-driven communication to strengthen relationships with consumers. In addition, product quality remains a key factor in building loyalty, including aspects such as taste, consistency, hygiene, raw materials, and comfort. Although Nou Coffee already uses high-quality coffee beans and a digital system, some customers perceive the taste and presentation consistency as unstable. This indicates that product quality is still the primary key to maintaining customer satisfaction and loyalty, even more important than technological convenience. The study employed a descriptive quantitative method. The population consisted of all consumers who had made purchases at Nou Coffee, totaling 10,122 customers. Using Slovin’s formula with a 95% confidence level and a 5% margin of error, the sample size was determined to be 385 respondents. The conclusion drawn from this research is that both partially and simultaneously, Customer Relationship Management (CRM) and Product Quality significantly influence consumer loyalty at Nou Coffee Shop.

Digital transformation (DT) and Big Data Analytics Capabilities (BDAC) enable SMEs to adapt to rapidly changing markets, innovate, and maintain relevance in the digital age. This research explores the impact of DT on SME performance through the lens of BDAC and innovation, from a multi-methods approach and applying the dynamic capabilities view. It asserts that simply investing in DT doesn't ensure enhanced performance. Analyzing 183 Spanish SMEs from various sectors, the study highlights the need for creating specific conditions that enable DT to positively impact performance. The integration of PLS-SEM and fsQCA methodologies provides a comprehensive analysis of BDAC as pivotal in optimizing SME performance through DT, emphasizing the necessity of strategic alignment with innovation. This nuanced approach, combining the predictive power of PLS-SEM and the configurational insights of fsQCA, demonstrates that investment in DT alone is insufficient without fostering conditions conducive to innovation. Our empirical insights offer actionable guidance for managers utilizing BDA or contemplating technological investments to elevate firm performance which go in the direction of increasing their innovation capabilities. Additionally, these findings equip policymakers with a nuanced understanding, enabling the design of tailored measures promoting DT in SMEs anchored in the nuances of BDAC and innovation capabilities.

Due to the global pandemic and world economy recession, the passenger flow of the retail industry is still relatively weak. Many countries have strengthened measures to prevent and control the epidemic, and then temporarily closed their stores. This reminds businesses that COVID-19 is still an ongoing challenge. This paper aims to identify the possible digital solutions for traditional offline retail stores to embrace digital innovation to become more smart and efficient. This research theme is to explore the feasibility of introducing a digitized business model into traditional retail stores using JD sports as the case. Business Model Canvas is used to identify the existing business model of JD retail shops, while Innovation Ambition Matrix is designed for making the innovation plan. The latest business model is presented with the help of the Customer Journey Map. By implementing the model, JD's traditional retail shop will reduce labour costs and increase operational efficiency, strengthening its competitive advantages.

: The global business environment changes very fast, forcing organizations to seek ways to improve their operational efficiency, cut costs, and enhance their decision-making. Optimizing performance is possible only with a clear understanding of how work gets done. It is here that well-defined business processes become very instrumental. However, for an organization to understand, evaluate, and eventually improve its processes, it is important that they model them in the first place. Traditional modeling techniques, such as BPMN and UML, provide a standard framework of visual and graphical representation for these processes. Most of these methods, however, fall short of capturing domain knowledge. The evolution of semantic web technologies has necessitated ontology-based business process modeling, which provides meaningful representations for business processes through the integration of ontologies. In this paper, an ontology-based business process model (OBPM) of the handicraft domain is presented focusing on the pastry-making field.

Objectives: The traditional Handicraft sector in Jordan is encountering significant challenges due to the measures adopted by the Jordanian government to curb the spread of COVID-19. These measures threaten the handicrafts sector’s sustainability and compromise artisans’ livelihoods. This research aims to examine the socioeconomic impact of COVID-19 on the Traditional Handicraft sector in Jordan. Methods: The research utilizes a qualitative methodology to collect and analyze data. The research attempted to cover mostly widespread handicrafts in Jordan. These crafts were concentrated in Jordan's capital 'Amman'. A random sample of craftsmen working in ceramics, mosaics, olive wood carving, embroidery, and accessories was chosen. Semi-structured interviews, with open-ended questions, were conducted to collect the essential data. Results: The research results revealed that the pandemic badly affected the business activity and operational environment.  The research also shows the low and marginal support workers within the sector received during the pandemic were not adequate to help the artisans. Furthermore, it shows a relationship between changing strategies in the conduct of business and the sustainability of the studios. Conclusions: The research concluded that changing the management strategies of the studios and the marketing methods for handicraft products greatly helped the sustainability of handicraft studios during the pandemic. The research recommends training the artisans to be familiar with the social media platforms and utilize those platforms to sell their products, training courses in e-marketing managerial, packaging, and design skills are highly recommended for building capacities of the artisans and sustaining their studios.

This research aims to conduct an in-depth and comprehensive exploration of the complex and non-linear process that occurs when shifting from manual to digital financial management platforms among Micro, Small, and Medium Enterprises (MSMEs) in Makassar City. The study specifically analyzes the sequential adaptation of electronic wallet (e-wallet/QRIS) usage and specialized digital accounting applications. This research addresses three main issues: (1) identifying the key internal and external motivators that initiate the transition, (2) elucidating the specific psycho-managerial phases MSMEs go through during implementation, and (3) analyzing the challenges—particularly cognitive load and financial literacy barriers—that impede the establishment of digital accounting practices. Utilizing a qualitative approach and a multi-case study design, the research involved comprehensive in-depth interviews and observational analysis with 20 owners/managers from various MSME subsectors (culinary, retail, and handicraft) in Makassar over a nine-month period. The findings reveal the transition as proceeding through three distinct yet interconnected phases: Market Pressure and Necessity, Functional Digital Adoption (E-Payment), and Cognitive Institutionalization (Digital Ledger). It was consistently found that limitations in financial literacy—specifically, a low understanding of basic accounting principles—as well as the perceived complexity of application interfaces are the primary hindering factors for full digital integration. Driving factors include market competitiveness, service speed, and the automatic separation of business and personal funds. This study provides important policy implications for creating focused and practical digital literacy programs, contributing significantly to the development of Islamic Education Management by emphasizing the need to integrate digital accounting skills with entrepreneurial ethics to ensure the sustainability and financial transparency of MSMEs

Goal: The Covid-19 pandemic has had an impact on the handicraft sector, as efforts to promote it have stalled. Purchase intention is reduced and business is sluggish. This condition provides an idea to be able to innovate in order to maintain the existence of the handcraft business. Practically, the handicraft industry is heavily affected by the declining tourism effect because many of its consumers come from abroad. The traditional nuance is closely related to handicrafts, so many tourists like it. Findings : As a strategy for industry resilience, innovation supports these business people. This research examines how industry players collaborate with many parties and what innovation are being made to deal with the Covid-19 widespread in the business people in the handicraft industry in 2021 in the Central Java region of Indonesia. Results: The results show that innovation with collaboration has an impact on business resilience and gives management strength to be able to make recovery. Supported by government policies, the recovery better. Suggested: the innovation can be deeply focusing on the process and also management to ensure the resilience.

E-commerce has, within a short time, completely transformed the traditional retail business models. The emergence of online platforms has altered the consumers' purchasing mindset to favor quick and easy shopping, a larger selection of products, and simple price comparison. This transition has prompted physical stores to struggle with fewer visitors and stronger competition as one of its major cons. Customer preferences, pricing, marketing, and supply chain management: e-commerce's effect on traditional retail. Besides, studies look into the extent to which physical stores are adopting by means of digital integration and hybrid models like online ordering and in-store pickup. Based on the most current data and reports from 2025 onward, the paper points out that e-commerce, despite being a major disruptor in the traditional retail sector, also opens up another door for new growth, innovation, and business transformation. Keywords: E-commerce, Retail, Consumer Behavior, Business Models, Online Shopping

PurposeSmall businesses are facing evolving environments, with a resulting need to shift their traditional approaches toward new business models (BMs). Many face difficulties within this transition process due to their specific resource constraints. Based on this, incremental changes to the BM – business model transition (BMT) – are proposed as comprising a suitable framework for entrepreneurial small businesses.Design/methodology/approachThis study conducts a systematic literature review (SLR) to cover a broad range of relevant literature within a final sample of 89 articles. The SLR method was chosen to integrate research in a systematic, transparent and reproducible way. For qualitative analysis and framework derivation, the study draws on a thematic ontological analysis.FindingsThe broad search criteria, focusing on BM, incremental BM changes and small businesses, pave the way for a comprehensive overview of multiple research streams of BM concepts (e.g. digital and sustainable BM). The main contribution of this work is the resulting holistic BMT framework, comprising the main parts BM innovation, external antecedents (transition of environment, entrepreneurial ecosystem), internal antecedents (dynamic capabilities, entrepreneurial orientation, resilience, strategy) and output (firm performance).Practical implicationsThe framework provides guidance for entrepreneurs and entrepreneurial managers to implement and complete BMT in small businesses. Furthermore, the presented paper sets a future research agenda focusing on small businesses structured according to the derived framework.Originality/valueThis study provides the first SLR of existing BM concepts with a small-business specific perspective on BMI and a focus on various incremental BM changes.

This article is devoted to the issues of transition to «Industry 4.0» technologies at enterprises of traditional sectors of the economy. The introduction of Industry 4.0 achievements sets trends for transformation and significant improvement of production processes in order to increase their efficiency and safety. The author examines the issues of integrating digital solutions into the technological processes of enterprises and the use of artificial intelligence, which is becoming an integral element of the modern industrial era. The main role of artificial intelligence is to create intelligent systems capable of automating and improving a number of operations in production. At the same time, the possibilities and prospects of using artificial intelligence are considered, and the main challenges and problems associated with the introduction of artificial intelligence into the production processes of industrial enterprises are analyzed. In general, the application of key aspects of Industry 4.0 is a complex process in the field of science, technology and technology, and in this regard, the relevance of researching possible ways to solve emerging and potential problems of expanding the digital transformation of the manufacturing sector and the introduction of Industry 4.0 technologies into production is increasing. The purpose of this article is to show the relevance and timeliness of the use of digital solutions in business processes, to analyze the possibilities of using the achievements of Industry 4.0 in enterprises of traditional industries and to consider the challenges and problems that arise. As a result of the analysis, it can be concluded that in modern Russian companies, the introduction of digital technologies has become a necessity to increase the competitiveness and profitability of business, develop new directions and expand production potential.

As a distinct component of the local economy, Weifang’s traditional handicraft sector not only contains countless intangible cultural heritages, but it also serves as a significant driving force in encouraging local economic progress. However, the establishment of a brand system is a vital step toward upgrading, cultural inheritance, and commercial expansion in the handicraft business. However, most handcraft brands in Weifang have poor brand construction, slow development, and even shrinking. This essay, written in the context of the sector 4.0 era, examines the current state of the branding process in the Weifang handicraft sector. It examines the path of brand systematization construction in the Weifang handicraft industry from multiple perspectives, including brand awareness, brand positioning, brand derivation, and brand communication, with the goal of encouraging creative transformation and innovative development that meets contemporary needs.

Assam has able to gain a remarkable place in the global forum for its unique and beautiful handicraft. The historical facts, religious and traditional values, social customs, cultural background, are reflecting in the handicraft of Assam. With the advancement in the field of technology digital marketing played an important role almost in every field. Digitalization help in market expansion, improves sales, create product awareness, improve design, personalized product etc. The previous literature shows that handicraft business is spreading more widely through digital marketing. The present study focuses on the growth of handicraft business through the application of digital marketing. For this the study selects Barpeta and Nalbari districts of Assam. As artisans of both the districts has specialization for producing some unique handicraft product such as cane and bamboo, pottery, assamese jewellery, firecrackers, bell and brass metal products. The total sample size is 100. For collecting primary data interview schedule has been used. The secondary data has been collected from previous research articles, journal, reports etc. The findings show the digital channels adopted by the artisans, its impact on income, expenditure and profit. The study found artisans are mostly familiar with social media platform as compared to e-commerce platform.

In consequence, the idea of resurrecting the Indian traditional handicraft through e-commerce and global circuits has revolutionized the handicraft industry and secured business viability for artisans. Handmade traditions of Indian fabrics, pottery, metals and woods formed a strong history which has had problems like falling customers, an influx of the industrial and machinery products and shrinking number of artisans. However, recent mega online markets such as Amazon, Etsy, E-tails, and exclusive Indian sites, etc., are helping small artisan groups to straight away through their products to the international markets without involving several middlemen and retrieving actual prices a bit. Schemes like Make in India, Vocal for Local, and One District One Product (ODOP) are helping to teach local artefacts to the world. Increasingly, traditional marketing approaches are complemented with social media and modern techniques help bring particular attention to artisans and their creations. However, illustrating these opportunities, digital literacy, logistic issues, control over product quality, and fairtrade practices still pose a huge problem. Drawing from the case of e-commerce, trade policies and interventionist measures in this paper, the author looks at how the artistry can have a sustainable environment in Tanzania. This exposes the weakness in skill development, fund and infrastructure for handcrafted product industries in India for a sustainable future in the IT enhanced global market.

The digital transformation of traditional culinary businesses has become a critical pathway for achieving sustainable growth and competitiveness in the digital age. This study explores how these businesses transition to online platforms, the challenges they face, and the benefits they achieve. A mixed-methods approach was employed, combining qualitative interviews with traditional culinary business owners and quantitative analysis of business performance data before and after digital adoption. The study also examined case studies of businesses successfully utilizing digital tools such as food delivery platforms, social media marketing, and AI-based analytics. Findings reveal that businesses adopting digital tools experience significant growth in revenue (up to 40%) from 2019-2024, improved operational efficiency, and enhanced customer engagement. However, challenges such as a lack of digital literacy and initial investment costs remain substantial barriers. Successful case studies demonstrate that leveraging partnerships with delivery platforms and effective social media marketing are key strategies for success. Digital transformation provides opportunities to widen market reach, preserve culinary heritage, and enhance customer experiences. To overcome barriers, governments and private organizations can play a role by offering training programs and financial support. The integration of advanced technologies like AI and data analytics also shows promise in driving efficiency and personalization. The digital transformation of traditional culinary businesses is not merely a trend but a necessity for long-term success. Despite challenges, the benefits of increased visibility, operational improvements, and customer satisfaction outweigh the costs, making digital adoption a viable strategy for traditional culinary enterprises.

Objective: This study examines the intersection of cultural heritage and digital transformation by analyzing technology adoption in Minangkabau’s traditional SMEs, focusing on Kampung Rendang in Payakumbuh and Kampung Tenun Pandai Sikek. The research investigates how digital capital—comprising access, skills, and integration—shapes this transition while maintaining cultural authenticity.   Method: A qualitative comparative method was employed, involving 35 informants, including SME owners, workers, and key stakeholders. Data collection was conducted through in-depth interviews, direct observations, and document reviews. The analysis explored digital adoption patterns and challenges in both business clusters.   Results and Discussion: Findings indicate that 83% of Rendang SMEs and 73% of Tenun SMEs have incorporated digital technologies, primarily in social media and e-commerce marketing rather than full operational integration. Major challenges include limited digital literacy, inadequate training, and security concerns. Kampung Rendang exhibits a higher degree of digital adaptation, leveraging technology for international market expansion, whereas Kampung Tenun prioritizes traditional craftsmanship, restricting digital adoption to promotional activities. The research highlights the influence of Minangkabau’s cultural values in shaping technology adoption decisions.   Research Implications: The study underscores the need for sustained digital training, government incentives, and strategic collaborations to enhance digital competencies while safeguarding cultural heritage.   Originality/Value: This research provides empirical insights into how traditional SMEs can integrate digital technologies while preserving cultural identity. By balancing heritage and innovation, Minangkabau’s SMEs can enhance global competitiveness while maintaining their unique traditions.

This research paper explores the integration of e-commerce and social media in the marketing of Jaipur's traditional handicrafts. The study investigates how these modern technological tools are being utilized to promote and sell handcrafted products, bridging the gap between centuries-old artisanal traditions and contemporary digital platforms. Through a mixed-methods approach, including surveys, interviews, and case studies, the research examines the impact of e-commerce and social media on sales, brand awareness, and the preservation of Jaipur's handicraft heritage. The findings reveal significant opportunities for artisans and businesses to expand their reach and enhance their marketing strategies, while also highlighting challenges in adopting and effectively utilizing these digital tools.

Research methodology The case study is based on field data including semi-structured interviews with the main protagonist and related stakeholders of Karan Handicraft, a leather craft artisan enterprise. After informed consent, the interviews with the craft artisan entrepreneurs of Karan Handicraft were conducted, transcribed and analysed verbatim in the respondents’ native language, Kutchi Gujarati. The authors also used archival data given by the company. In addition, secondary data from industry reports and business magazines was used to create the case. Case overview/synopsis The case investigates the impact of digital technologies on the small handicraft artisan entrepreneurs by focusing on a family-run business of a leather craft. It traces the evolution of Karan Handicraft, based in Kutch district of Gujarat, India from the year 2007 to 2023. The third-generation artisan entrepreneur Karan Marvada attempted exploring the new-age social media platforms to showcase the products, modified his product designs to attract a new customer-base and adapted to digital marketing. However, in the wake of the crowding in the handicraft cluster, the central business problem that Karan was grappling with was, if he should scale up his artisanal entrepreneurial stint using electronic commerce (e-commerce) as a medium. Another allied issue is in such a scale-up, should he use e-commerce, i.e. as a medium of communication only or as a medium of both communication and delivery. While the latter may lead to scale, it may raise the challenge of not being able to preserve the traditional values of his ancestral business. Complexity academic level This case involves various issues that arise in entrepreneurship management, such as decisions related to growth strategy (remain small and unique vs become large and mass scale), to maintain a physical presence vs digital presence and the form of digital presence, are dwelt upon. The case is aimed at graduate students in an entrepreneurship or family business course. It could also be taught in other courses that focus on innovation and social entrepreneurship.

This study evaluates the implementation of the job order costing method in traditional crafts. The originality of the research lies in the detailed mapping of production costs using job order costing in traditional culture-based handicraft businesses, which are still relatively limited in previous research. The purpose of this study is to evaluate the implementation of job order costing in determining the cost of production. The research method used is field research with a qualitative descriptive approach. Primary and secondary data were collected through observation, limited interviews, and documentation with data on the production and sales of traditional crafts in this case gamelan. Empirical results show that gamelan sales in the 2022–2024 period have decreased due to weakening buyer interest due to sluggish economic conditions. However, sales revenue is still greater than production costs, so the business does not suffer losses. Profit planning analysis shows that by 2025 businesses must sell at least eight sets of gamelan to achieve a profit target of 20%. The implications of this study show that the implementation of job order costing can help MSMEs in improving the accuracy of profit planning, cost control, and business sustainability.

The paper is an important contribution to scholarship on the relationships between online communities and entrepreneurial initiatives for business-to-consumer (B2C) in the traditional artisan market. The development of social networks based on information and communication technologies is creating the premises for a fluid circulation of people, ideas, and goods, turning the world into a “global village” (Nevzat, 2018). There is a growing market related to the handicraft industry, including the ones related to local traditions and customs. There is an increasing interest in this market, with the cultural sector representing 3.1% of the global GDP and 6.2% of job vacancies (UNESCO Launches… | UNESCO, n.y.). In 2022 the market for artisan market was valued at 752,2 billion USD with an expectancy of 1296,6 billion USD by 2028 (Research and Markets, n.y.), while the yarn and needle arts, that this research is studying, represent a 3 billion USD market in the US (GITNUX, 2023). Business in the artisan field is thriving around the world, bringing together unique local flavours and global communication channels, especially through social media. Even if, from history, the village area was the place for small initiatives and family-run businesses related to traditions and customs, the concept of business modelling in this market is still under development. This paper aims to clarify the role that social media has in defining entrepreneurial initiatives in the field of handicrafts and how online communities are supporting these activities, using the guidelines from Business Model Generation (Osterwalder et al., 2010). Data collection was carried out using netnography framework (Kozinets, 2010) by observing and analyzing the messages from online communities and other online public information and documents (Bowen, 2009). The study draws some conclusions and findings together with limitations and potential new research directions.

This paper presents the design and implementation of Kstitch: a Smart Tailoring Management System with Real-Time Order Tracking, developed to digitize and modernize traditional tailoring operations. Conventional tailoring systems rely on manual record-keeping, which leads to issues such as data loss, inefficient order tracking, and poor customer communication. The proposed system is built using the MERN stack (MongoDB, Express.js, React.js, Node.js) and introduces a dual-role platform for both customers and tailors. It enables digital order management, multi-item garment handling with flexible measurement inputs, and portfolio-based tailor discovery using geo-location features. A key contribution of this system is its offline-first architecture, where order data is temporarily stored in local storage when the backend server is unavailable and automatically synchronized once connectivity is restored. This ensures uninterrupted workflow, particularly in environments with unstable network conditions or server downtime. The system also integrates features such as JWT-based authentication for secure access, Cloudinary-based image handling for portfolio management, and automated WhatsApp communication for order updates and invoice sharing. The implementation demonstrates improved efficiency in order handling, enhanced customer experience through real-time tracking, and reduced dependency on manual processes. This solution provides a scalable and practical approach for small and medium-scale tailoring businesses to transition into a digital ecosystem while maintaining operational flexibility

This study aims to design and develop a Point of Sale (POS) system tailored to the operational needs of Purna Sembako, a micro retail business located in a rural area. The main issue addressed is the store’s continued use of manual transaction recording, which causes inefficiency, data entry errors, and delays in reporting. The research follows a Research and Development (R&D) approach using software engineering methods. The development process includes needs analysis, web-based system design, implementation of transaction recording, inventory management, and sales reporting features. Black box testing was employed to validate system functionality, while user evaluation was conducted using a Likert-scale questionnaire involving the store owner and staff to assess usability, efficiency, and user satisfaction. The testing results indicate that the system operates as intended, and user evaluations rated the system as “Good” to “Very Good” across all aspects. The developed POS system proved effective in improving operational efficiency and data accuracy, while also contributing to digital transformation in small-scale retail enterprises.

AI-driven personalization has become a critical competitive advantage in modern retail environments, enabling tailored customer experiences across digital and physical touchpoints. This article explores the transformative role of artificial intelligence technologies in reshaping consumer goods and retail personalization strategies. Beginning with an overview of fundamental AI personalization technologies, the discussion progresses through advanced recommendation engine architectures, dynamic pricing implementations, conversational AI systems, and in-store personalization solutions. The article examines how these technologies create cohesive personalized experiences that increase engagement, drive sales, and foster customer loyalty while addressing technical challenges and implementation considerations for retailers navigating the evolving digital commerce landscape.

The COVID-19 pandemic has significantly reshaped China’s social and economic landscape, accelerating the shift toward e-commerce and prompting traditional retailers to establish online platforms. This transition has intensified competition among online stores, necessitating that merchants enhance customer trust and improve the overall shopping experience. This article examines effective strategies to optimize visual elements—such as web design and layout—to bolster consumer trust and increase purchase intentions. Through document analysis, it identifies prevalent challenges in the online shopping experience, including inaccurate information and poor interface design, assessing their detrimental effects on consumer behavior and overall store performance. The article also offers practical solutions aimed at addressing these issues, such as enhancing logo visibility, refining design and color schemes, ensuring accurate and diverse product information, implementing AI-driven shopping guides, and tailoring web design to specific target demographics. These strategies ultimately aim to enhance the market competitiveness of online retailers in an increasingly crowded marketplace.

RideSmart is a web-based tool designed to provide JavidsonMotorshop clients with personalized product recommendations, including appropriate motorcycle parts, accessories, and services. To create recommendations that are specific to each user, the system examines purchase histories, product qualities, and consumer preferences using TF-IDF (Term Frequency–Inverse Document Frequency) and descriptive analytics. Compared to generic promos, this not only expedites and enhances the shopping experience but also provides insights into consumer behavior, including demand trends, buying habits, and popular products, which aid the store in improving its marketing and stocking plans. The RideSmart recommendation system for JavidsonMotorshop uses TF-IDF to extract key features and keywords from customer reviews and searches, enabling personalized motorcycle product suggestions that improve purchase decisions and customer experience (Huang, 2025). Descriptive analytics complements this by analyzing historical sales, browsing behavior, and product interaction data to identify trends and patterns, supporting data-driven marketing and inventory management (Harvard Business School Online, 2021). Together, these approaches allow the system to tailor recommendations to individual preferences, enhancing sales efficiency and operational effectiveness (Sigma Computing, 2025; MEEGLE, 2025).Laravel, a PHP framework, Python, MySQL, and front-end technologies (HTML, CSS) are used in the technical implementation of RideSmart. Functionality (accurate product details and seamless search, cart, checkout, etc.), reliability (availability and recovery from errors), efficiency (page load speeds, resource usage, handling many users), usability (intuitive navigation, responsive controls, design), and portability (ease of deployment on other servers or in other locales) were the main dimensions that were examined in order to assess its quality using the ISO 25010 standard. Both "technical" and "user" respondent groups evaluated the system: technical respondents emphasized functionality, dependability, and performance, particularly the accuracy and pertinence of recommendations made possible by TF-IDF and analytics, while users prioritized usability, acceptability, and enhancements to day-to-day operations (particularly streamlining product search and enhancing customer satisfaction). The evaluation provides a fair perspective because the respondents are a combination of about 60% users and 40% technical stakeholders. Although there is room for improvement, overall, the results show that RideSmart is technically sound, practically helpful, and effective in real-world situations. Among the suggested enhancements are enhancing and preserving theunderlying data (for both products and users), integrating diagnostic or external tools for more precise compatibility, allowing recommendation adjustments based on a customer’s mechanical expertise, broadening the product database, adding multilingual support, incorporating user feedback into the recommendation loop, and creating a mobile‑friendly version to extend reach and usability.

This study explores the readiness of Micro and Small Enterprises (MSEs) in Mexico, specifically grocery stores, to implement the Virtual Value Chain (VVC) through Information and Communication Technologies for Development (ICT4D). A mixed-methods approach was used, combining diagnostic tools, structured surveys, and interviews. Quantitative data were analyzed using descriptive statistics, correlation analysis, and machine learning to identify digital adoption patterns. The results indicate that limited technology adoption remains the main obstacle to VVC integration. Significant associations were found between digital engagement and the age and educational level of store managers. Key digital gaps persist in inventory control, supplier coordination, and demand forecasting. Although machine learning models did not significantly outperform baseline predictions on willingness to adopt technology, the findings emphasize the potential of targeted training and accessible mobile solutions. The study proposes a new diagnostic and predictive framework to assess VVC readiness in low-resource contexts. It shows that ICT, when strategically aligned with business operations and paired with adequate training, can enhance sustainability and livelihoods. Although the study is limited to one geographic area and one business sector, it offers a foundation for scaling similar initiatives. The findings support context-sensitive strategies and capacity-building efforts tailored to the realities of MSEs in emerging economies.

ABSTRACT The online-to-offline (O2O) business mode has on-demand features to offer consumers instant fulfillment from a local store upon their online order. The O2O mode has attracted many more consumers recently. Using empirical evidence from a leading O2O platform in China, our study focuses on the market entry issue in the O2O context. Upon the new entrant entering the market, existing listed sellers implement a higher overall promotion to their consumers by enlarging the direct promotion extent but reducing the other types of promotions, including coupon, bundle, quantity, and gift promotions. However, the O2O platforms reduce the promotions level to the consumer orders from the existing listed sellers. The platform’s and existing listed sellers’ promotions increase consumers’ purchase frequency but lower their purchase amount per order. The extent of these impacts depends on the geographic location of the new entrant. Our findings provide guidelines for the O2O platforms and listed providers to implement appropriate promotion strategies to attract consumers when considering the impact of certain new providers entering the O2O market.

Globalization and digital innovation have changed consumer spending habits in the fashion industry. Online shopping is very convenient, as it can reach consumers globally and has become a new norm in today's life. With the rapid advancement of technology, the retail and fashion sectors have seen a significant boost in online performance, providing a better online shopping experience. However, one crucial challenge remains: accurately determining clothing sizes. Traditional size charts and manual measurements often result in inconsistencies, leading to high return rates and customer dissatisfaction. This has driven the need for more sophisticated solutions, such as the implementation of artificial neural networks (ANNs) for efficient apparel cloth sizing. By analyzing customer measurements and preferences, ANNs can tailor size recommendations, enhancing the online shopping experience. This technology not only reduces return rates but also builds customer trust and loyalty, as they are more likely to receive well-fitting garments. Furthermore, efficient sizing algorithms can streamline inventory management for retailers, ensuring that the right sizes are stocked and reducing waste, which can represent a significant step towards more sustainable and consumer-centric retail practices. There is a great deal of room for more advancements in this field as technology develops, promising a future where online clothing purchases are as reliable and satisfying as in-store experiences. The ANN model used in this research achieved an accuracy of 62.8% in size prediction, with recommendations for further improvements through larger datasets and additional predictive features.

This research presents a comprehensive approach to customer segmentation using Recency, Frequency, and Monetary (RFM) analysis, combining statistical insights, data visualization, and machine learning techniques. The study utilizes a real-world dataset obtained from a retail environment, aiming to categorize customers based on their recent purchasing behavior, visit frequency, and monetary contributions to the store. The code begins with data preparation and exploration, ensuring data integrity by addressing issues such as negative quantities and missing customer identifiers. Following this, the Recency, Frequency, and Monetary metrics are computed, providing a holistic view of customer engagement and spending patterns. Visualizations, including violin plots, histograms, and box plots, are employed to intuitively convey the distribution of these metrics. The research then delves into the quantile-based segmentation of customers, allowing for a more granular classification. Quantiles are calculated to divide customers into four segments for each RFM metric. The resulting quantile labels are applied to the dataset, enabling the creation of a compound RFM quantile that combines recency, frequency, and monetary information. This combined quantile facilitates the definition of distinct customer segments. To further enhance the interpretability of customer segments, the study introduces a set of rules for labeling customers based on their RFM quantiles. These rules yield segments such as "Best Customer," "Loyal Customer," "Big Spender," "Dead Beats," and "Lost Customer." The resulting customer segmentation is presented visually through histograms and a pie chart, providing a clear and concise representation of the distribution of customers across different segments. Moreover, the research integrates machine learning models, including XGBClassifier, and CatBoostClassifier, to explore the potential of automating the segmentation process and predicting customer segments based on historical data. However, the machine learning aspect is introduced with commented-out sections, leaving room for further exploration and experimentation. In conclusion, this research contributes a comprehensive and detailed code implementation for RFM-based customer segmentation. The integration of visualization techniques aids in the interpretation of customer behavior, while the inclusion of machine learning models opens avenues for predictive analytics in customer segmentation. The presented approach provides valuable insights for businesses seeking to tailor marketing and customer relationship strategies based on individualized customer segments. KEYWORDS— Customer Segmentation, Frequency, Monetary Value, Recency, RFM Analysis.

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By adopting the Online to Offline (O2O) commerce strategy, this paper designs and implements the Bluetooth Low Energy (BLE) indoor positioning technique for an Android APP to let the customer browse online and promote the offline shopping conversely. This APP supports Bluetooth indoor positioning, multi-floor route planning, push message notification and various feedback mechanisms. Hence, it is able to locate current position of the customer in the department store and navigate the customer to each retailer for buying the commodities ordered online through the shortest path.

As the new retail has come, a lot of retailers try to make a digital transformation. The new retail begins with the development of an online to offline (O2O) mechanism to extend their online e-commerce to offline retailers. Nowadays, leading new retail players have been actively investing in offline retailers. Furthermore, they also evolve around technology-driven sales and cost efficiency to create online merge offline (OMO) services. This study used the Buynow Shanghai flagship store as an example and presents how to design and evaluate mini-programs for creating new retail OMO services for retailers. This study begins with the focus group interview to the three main business departments of the Buynow Shanghai flagship shopping mall. Then, we implemented a quality function deployment (QFD) analysis by referring to the interview results. Thirdly, we proposed the main functions, which can create the OMO service, of the mini-program prototypes by referring to the development priority proposed in QFD analysis. Finally, we design the user interface of the mini-programs and edit a simulated operational video to provide comprehensive introduction of the mini-programs and implemented the system usability scale (SUS) test to sample users. The results of this study show that the mini-programs can enable offline retailers to create omni-channel to customers. They also simplify and save time for the consumer's shopping experience. Furthermore, it allows for better data collection and data analytics for big retailers. The future studies will focus on using Kano's model to evaluate the customers' satisfaction of the services provided by the mini-programs..

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In order to improve the design efficiency of dress, to shorten the production cycle, and to meet the rapid design needs of customers for customized garments, a design method of dress for Mass Customization (MC) was proposed. The different styles’ parameterized clothing models were built based on the technology of Tabular Layouts of Article Characteristic Table (TLACT) and AUTOCAD and the variant design of the clothing prototype models were realized with the parameterized method. A customized design platform for the dress was developed to quickly generate variant garment models to respond to customer needs. The results show that this method and the design platform of the dress can more efficiently mass-produce customized clothing.

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The deep integration of Internet, intelligent manufacturing and big data technology has promoted the development of products to be networked, digital, intelligent and personalized. The rapid iteration and differential segmentation of consumer demand has spawned new personalized consumer demand, transforming the traditional manufacturing model into a service-oriented manufacturing model. This paper analyses the large-scale customized operation mode of domestic and foreign clothing custom brands. In view of the transformation of traditional clothing industry, this paper proposes a solution to establish a large-scale custom clothing architecture under the vision of intelligent manufacturing cloud platform technology. This paper uses data mining and cloud computing and other methods to build an “Internet + manufacturing” innovation model with rapid collaboration under the umbrella of big data, and propose an architecture for mass customization of clothing, providing effective solutions and strategy recommendations for the transformation and upgrading of the traditional apparel industry.

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“Bespoke,” or mass customization strategy, combines demand learning and preference learning. We develop an analytical framework to study the economic value of bespoke systems and investigate the interaction between demand learning and preference learning. We find that it is possible for demand learning and preference learning to be either complements or substitutes, depending on the customization cost and the demand uncertainty profile. They are generally complements when the personalization cost is low and the probability of having high demand is large. Contrary to usual belief, we show that higher demand uncertainty does not necessarily yield more complementarity benefits. Our numerical study shows that the complementarity benefit becomes weaker when customers are more strategic. Interestingly, the substitute loss can occur when the personalization cost is small and the probability of having high demand is large, when customers are strategic. The online supplement is available at https://doi.org/10.1287...

Recognition of clothing categories is an appealing study to emerging applications such as computer aided fashion design for mass customization and e-commerce. In the study, the description and classification of clothing styles is established based on the preference index heuristic. Specifically, we take advantage of consumer’s visual perception of clothing and their free choice description to; understand, characterise and, classify clothing styles. Evaluated on a dataset with 60 style samples of male clothing, the procedure demonstrates promising results in recognizing five clothing categories. Keyword: Clothing, Semantic Attributes, Heuristics, Styles, Computer-Aided Fashion Design

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Purpose3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.Design/methodology/approachA business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.FindingsFirst, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.Research limitations/implicationsThe new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.Practical implicationsThe new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.Originality/valueA new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

Mass Personalization (MP) is being adopted in the apparel industry to provide customized product solutions to the customer. Customer co-creation is the key opportunity provided during the initial design phase. The best way to evaluate these new products is to create virtual prototypes based on the digital environment. Therefore, this article examines the digital approaches to the development of apparel prototypes by systematically reviewing the literature. The findings reveal that existing digital approaches are primarily aimed at visualizing a new product based on a 3D avatar created using scanned body measurements of a customer, although user experience is required for evaluation. The most important factor in the design process is the digital solutions to enhance the user experience of the new product (comfort of clothing) in its infancy. Therefore, this study explores digital technologies used in other industries to get an understanding on the possibilities of adopting the same in the apparel industry.

The fashion industry is constantly evolving, and new technologies are playing an increasingly important role in shaping the way clothing is designed, produced, and consumed. One technology that is gaining attention in the fashion industry is 3D body scanning. This technology uses sensors and cameras to create a digital representation of a person's body measurements, which can be used to create custom-fit clothing and improve the fit of mass-produced clothing. In this paper article, we aim to explore the impact of 3D body scanning technology on the downstream apparel supply chains, including the benefits, disruptive changes, risks and challenges, and limitations of the technology, based on literature review analysis. The analysis results suggests that 3D implementation can effectively improve garment fitting, reduce waste, and enable customization, resulting in enhanced customer satisfaction and environmental sustainability.

With the intensification of global market competition and the continuous development of the information technology, competition in the apparel market has become increasingly fierce. The key to whether China's garment industry can maintain its advantage in the international market competition in the future lies in whether it can promote and realize the informatization of the garment industry or not. After all, under the context of increasingly developed information technologies and growing competition in the garment market, mass customization of garments has become a future trend in the garment industry. As custom-made clothing is more in line with consumers' individual needs in terms of style, fabric, and size, the focus of development for clothing companies is increasingly on the grasp of the fit of clothing. However, with China's large population and the wide variety of body types, traditional hand-made garments are time-consuming and cannot meet the differentiated needs of consumers in the modern market. The design of garment samples is an important part of the industrial production of garments and is highly dependent on the skills and experience of the operators. In other words, the level of technical expertise can determine the quality and shape of a garment product to a certain extent. As a result, in order to further improve the efficiency and quality of garment sample design and to reduce the dependence on operator skills and experience, this study proposes an intelligent garment paper sample design system based on BP neural networks. The system mainly utilizes the self-learning, self-organizing, and adaptive as well as nonlinear mapping functions of artificial neural networks to design clothing samples autonomously, thus improving the design efficiency. In the era of rapid development of information technology and artificial intelligence technology, the development of intelligent garment pattern design systems with independent intellectual property rights is of great significance in promoting the prosperity of the garment industry.

Today, in the mass customization production environment, clothing companies face even more difficulties, such as the rapid and uncertain changes in customer requirements and their impacts on production time, cost, and quality of product. In order to survive and develop in such a competitive environment, apparel companies should clearly identify customers' demands in the development of new clothing products. Understanding customer demands and their purchasing process is the base knowledge required to ensure successful marketing activities. However, customers' demands and behavior are affected by many factors, some of which conflict with each other in the production process. Therefore, an understanding of consumers' critical evaluative criteria when purchasing clothing products is one of the most important issues in the new product development process. The purpose of this paper is to determine the clothing product attributes that are of greatest value to customers and predict consumer preferences for attributes by applying the conjoint analysis method. The final results showed that five criteria have the most influence on shopping customers' behavior, including design, fabric/fiber style, color, form, and price. These findings can support apparel managers in the new product development process.

This research paper examines the intersection of bespoke tailoring and modern omnichannel retail, highlighting both its potential and challenges. This study explores the design and development of a custom tailoring tool. This tool has the potential to integrate the convenience of online shopping with the personalized fit of traditional tailoring. This paper addresses the issue of increasing demand for personalized clothing alongside the constraints of existing online retail platforms. The proposed solution involves a user-friendly, integrated platform designed to accurately capture body measurements and convert them into custom garment patterns. This tool has potential applications in creating bespoke suits and dresses, as well as in producing perfectly fitted everyday clothing. This study also investigates the potential positive effects on customer satisfaction, decreased return rates, and sustainability within the fashion industry. In conclusion, I will discuss the potential for future development and how this tool may adapt to the evolving requirements of the fashion industry.

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On-demand manufacturing is integral to sustainable practices, but product returns must be avoided to reduce waste and maximize revenue streams. With garment fit being a driving cause of returns, concerted technological engagement has been directed at acquisition of data defining apparel fit. (e.g., radial ease, compression ease, fit preference, body-shape, fit mapping, etc.) Such data has somewhat improved size selection algorithms but shed little insight on quantifying fit at the garment pattern level. For example, while a flattened 3D body mesh effectively reveals the body as 2D geometry, it offers little toward the developable garment pattern as it lacks relevance to established principles of dart manipulation and pattern-making theory. This paper discusses how a ‘block comparison’ approach to fit assessment better translates body data to linear dimensions suitable for both changing fit at the pattern level and improving fit prediction algorithms. Discussion will elaborate how body-blocks define 3D human morphology at the garment pattern level to establish practice for quantified fit theory while supporting traditional apparel pattern practice. The change management required for fit validation (the digital asset as tech pack) lays the foundation for automated mass customization, not as the once considered singular solution, but as a scope of solutions ranging from ready-to-wear (RTW) to bespoke. Not as the once considered singular solution, but as a scope of solutions ranging from ready-to-wear (RTW), to bespoke. With sustainable garment production being a key factor in mitigating climate change, fit validation to reduce garment returns (increasing the profitability of on-demand manufacturing) is a logical next step. In this environment, both customer and brand fit preference may align or differ without imposing on the other. From here we must consider that perhaps Industry 4.0 is better embraced with a full suite of fit intent offerings, where the change management required for RTW fit validation (digital tech packs) sets the foundation for automated mass customization, not as the once considered singular solution, but as a scope of solutions ranging from ready-to-wear (RTW), to bespoke. In this environment, both customer and brand fit preference may align or differ without

. Many companies have been expending considerable efforts to continuously improve manufacturing processes to ensure their competitiveness and remain in the market. Value Stream Mapping is a strategic tool that makes it possible to visualize the macro of production to assist in planning and decision-making. It is a process mapping that considers the workflow of a product from the arrival of the raw material to the result that is delivered to the customer. Despite the benefits this tool has provided to organizations, the time for its development is still very high, as its data is still filled manually, allowing its analysis to be error-prone. Digital technologies have brought several improvements to the methods and tools of organizations. With the goal of obtaining contributions to engineering through transdisciplinary approaches to decision support tools and methods, therefore, this study will present the development of a dynamic web application using data analytics and machine learning to visualize, identify bottlenecks, predict, and update data in current and future state mappings. Intelligent systems tend to eliminate the routine activities of engineering, so this application will allow engineers and technicians to dedicate more time to dedicate themselves exclusively to activities that require a more challenging level of managerial decision-making.

Agility is a central instrument for reacting appropriately to dynamic influences and enabling innovation capability. However, rigid production systems can no longer meet the requirements of agile product development and innovation processes. Flexible production systems like the 'Value Stream Kinematics' provide benefits for producing companies. In this research effort, the ‘Persona - method’ has been used to derive typical individuals who are influenced by a socio-technical system, specifically by a flexible production system. Based on these results holistic use cases of flexible production systems for the product development process and production system development were identified and described as well as discussed in detail. The comparison of agility barriers within industrial companies and the identified specific use cases of a flexible production system shows that agility barriers in product and production system development can be overcome by utilizing a flexible production system

Aim. The article is devoted to the study of intelligent systems and mechanisms that help an enterprise to quickly respond to changes in the external environment in competitive conditions.Methodology. The research examines the methods of adaptation of industrial enterprises to changes in the external environment as one of the serious strategic advantages in competition in order to meet market demand and achieve stable competitive positions.Results. Based on the results of the study, the need to develop new architectures of production systems with a high level of flexibility, new principles of organization and management of technological processes, including the creation of enterprises based on flexible production systems, is justified.Research implications. It is shown that for modern diversified industrial enterprises, the desire to increase production efficiency occurs due to the intensification and end-to-end automation of technological operations, computerization of technological and business processes, their coordination with transportation, warehousing and management operations along the entire chain of inter-company interaction and cooperation.

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We address a practical problem faced by many firms. The problem is deciding on the production levels for a product that has a very short selling season. The firm has a full period to produce and meet a lumpy demand which occurs at the end of the period. The product is no longer demanded after the end of the period. A constant production rate which minimizes average unit cost may increase holding costs. Varying the production rate at discrete points in time may increase production costs but may also decrease holding costs. In addition, allowing changes in the production rate enables the incorporation of forecast revisions into the production plan. Therefore, the best production plan depends on the flexibility of the production system and on the holding cost. In this paper, we formulate and solve a model of this production planning problem. Two models are developed to deal with two types of the average unit cost function. Numerical examples are used to illustrate the results of the model.

The flexibility and responsiveness of seru production have caught the attention of manufacturing and electronics industries. However, multi-skilled worker assignment poses a crucial and challenging decision-making problem for seru production systems. The existing literature on this problem for pure seru production systems primarily focuses on improving efficiency indexes, which often leads to an unbalanced workload among workers. To address this issue, this article investigates multi-skilled worker assignment for a hybrid assembly line-seru production system that comprises divisional serus and a short assembly line. To balance workload and optimize production efficiency, a bi-objective integer nonlinear programming model is developed. This model jointly optimizes worker-to-seru, worker-to-line, batch-to-seru, task-to-worker, and the processing sequence of each batch. A meta-heuristic method,  combining Non-Dominated Sorting Genetic Algorithm II (NSGA-II) with Multi-Objective Simulated Annealing (MOSA), NSGA-II-MOSA, is designed to solve the model. The results of numerical experiments demonstrate that the proposed model and solving method can greatly reduce workload imbalance while maintaining production efficiency. Moreover, NSGA-II-MOSA provides better Pareto solutions than three well-known multi-objective optimization approaches.

The current study aimed to recognize the effect of a just-in-time production system (JIT) on reducing production costs, especially in terms of serious competition, rapid technological development, and continuous changes in the business environment, which leads to an increase in paying attention to applying JIT on productive organizations. The most important findings of the study are that applying the JIT production system leads to reducing all types of inventory, which leads to improving the organization’s performance. Also, its application leads to the removal or reduction of activities that do not add value to the product, which is reflected in the reduction of direct costs in the organization. The study recommended the necessity of applying the JIT system by the productive organizations and becoming acquainted with the successful experiences of international organizations that adopt this system, with the need to alert production officials in organizations to organize the productive operations sites in a way that reduces production time, in addition to providing sufficient flexibility to reduce the time required for the production process and reduce production cycle.

CV. XYZ is a manufacturing company engaged in the textile industry producing t-shirts, cotton fabrics, and various other textile products. One of the business processes in the CV. XYZ is the production section. The main problems in the production section are the absence of a system that relates between production department and warehouse department in carrying out business processes and does not have any reports. Development of Enterprise Resource Planning (ERP) can be a solution for CV. XYZ. Odoo is one of open source ERP software that is widely used by various types of companies. The development of CV. XYZ uses the Odoo Quickstart Methodology. This methodology can implement the completion process on time and the costs needed can be adjusted to the project. The purpose of the development of CV. XYZ is to make their business processes can be accessed effectively and efficiently with the flexible production scheduling system. Once the ERP implementation is finished the system is measured using System Usability Scale (SUS) to measure the system usefulness based on the SUS result, the ERP implementation has succeed and acceptable.

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We present the flexibility of a human-centered production system called the seru production system (SPS). A theoretical framework for analyzing the flexibility of an SPS is proposed based on the input-process-output (IPO) system view. The enabling effect of workforce configuration on the flexibility of an SPS is explained. The flexibility of SPS is identified to be the capability of an SPS to have inclusiveness and variability. The inclusiveness shows the capability of an SPS to control-variability-with-stability, and variability presents its ability to control-variability-with-variability, which correspond to structural flexibility (SF) and reorganization flexibility (RF), respectively. We reveal that the SPS adopts SF as the main strategy to satisfy most demands and uses RF as an auxiliary means to capture unforeseen demands. In addition, our work reports the strategies for implementing SPS flexibility including structural flexibility strategy, reorganization flexibility strategy, and hybrid flexibility strategy.

Introduction:The study analysed the current situation of the microenterprise Arepas de Maíz Sarita in the city of Pasto, with the purpose of designing an administrative organisational structure that would boost its growth. It was proposed to establish clear roles through a manual of functions and procedures, which would improve efficiency and collaborative work among employees. This approach sought to strengthen the administrative process and increase business competitiveness.Development:Relevant background was drawn upon such as the work of Caicedo (2020), who designed a marketing plan to increase sales for a similar company. We also reviewed the research of Alpala et al. (2017), which implemented a production order costing system to improve decision-making. Finally, Bolaños et al. (2016) developed an export plan to expand the target market of an arepas company, providing internationalisation strategies. These studies provided valuable theoretical and methodological inputs to structure Arepas Sarita's improvement proposal.Conclusion:The analysis provided evidence of the importance of implementing a clear administrative structure in Arepas de Maíz Sarita. It was concluded that the organisational design, accompanied by a correct distribution of functions and market strategies, would strengthen its competitive position, improve its internal processes and generate greater economic benefits. The study provided significant contributions for the microenterprise, its employees and the regional environment.

This study aims to improve operational efficiency and financial management at Toko Pink 31 Surabaya by integrating two key components: store layout redesign and the development of a MySQL-based accounting system. The research uses a combination of qualitative and quantitative approaches through observations, interviews, system design, and simulations. The redesigned layout was developed using the Systematic Layout Planning (SLP) method and simulated via AnyLogic software to evaluate customer flow and service bottlenecks. The results showed significant improvements in space utilization, reduced customer congestion, and enhanced overall shopping experience. In parallel, the accounting system was developed using MySQL to automate and structure financial transactions. The system includes modules for product input, sales, purchasing, cost of goods manufactured (COGM) reporting, and daily financial summaries. The implementation of this digital accounting system reduced manual errors, streamlined transaction processing, and provided real-time access to financial data. The integration of both layout optimization and digital accounting demonstrates a comprehensive transformation model for SMEs, particularly in the retail sector. The findings emphasize that combining spatial efficiency and financial digitalization can significantly improve business performance, supporting broader efforts to digitalize micro and small enterprises in Indonesia.

No abstract available

This study aims to analyze the strategies adopted by traditional retail stores in Sidoarjo Regency to remain competitive amidst the rapid expansion of modern retail, particularly mini markets. Using a qualitative descriptive approach, data were collected through interviews, direct observations, and documentation involving five traditional store owners operating near mini market locations. The findings reveal that traditional retailers rely on several key strategies, including building strong social relationships with customers, offering flexible payment systems such as informal credit, adjusting product prices based on community purchasing power, and providing unique local products not found in mini markets. While these strategies help sustain competitiveness, challenges remain, especially regarding store management, layout, and limited use of digital technology. Therefore, collaborative support in managerial training, financial access, and technological empowerment is essential to enhance the competitiveness and sustainability of traditional retail businesses in the face of modern retail growth.

The advent of digital technologies in the fashion retail industry has completely changed the online shopping experiences, for customized apparel fit. In the fashion industry, virtual size and fit technologies are crucial for enhancing customer satisfaction. While China is leading by integrating fitting experience at Web 3.0 Metaverse, unlikely Pakistan the countries who do not utilize these technologies are still functioning on Web 2.0. At the same time, the lack of size and fit visualization tools renders personalization, making it evident that there is a huge technological concern that needs addressing in Pakistani Fashion E-commerce. This study focuses on exploration and evaluation of the digital anthropometric technologies on improving size and fit features in the fashion industry. In particular, it studies how Chinese fashion interfaces employ advanced technologies compared to the conventional systems used by Pakistani brands in order to improve customer satisfaction and promote mass customization. The selected Pakistani fashion brand websites were compared with technologically advanced Chinese fashion platforms. The evaluation was done on their use of digital tools, fitting systems, and integration of Web 2.0 and Web 3.0 Metaverse. It has been observed that Chinese platforms have embraced Web 3.0 technologies, which incorporates metaverse environments, whereas Pakistani fashion brands largely use Web 2.0 technologies that have limited interactive features. The deployment of Web 3.0 metaverse helps in global luxury branding, enhancing interactive customer environment. In order to be competitive in the global market, the Pakistani fashion retailers should incorporate new digital technologies as proposed by the findings. Embracing size and fit solutions not only supports sustainable practices like made-to-measure garments but also paves the way for scalable mass customization and digital fashion commerce. Keywords: E-commerce, Digital Technological Advancement, Mass Customization, Virtual Size and Fit Recommendation, Metaverse, Web 3.0 Technology

The retail sector is in a continuous effort to bridge the gap between online shopping convenience and the in-store sensorial experience, which is why up to 30 percent of high context products in the retail industry are being returned. To provide an opportunity to visualize products in AR using a Web-based platform and to avoid a native application, we present the Augmented Shopping Experience (ASE) framework based on WebXR and AR.js. Our offering is a markerless AR solution with a hybrid tracking adapter able to draw up to 60 frames per second on the mid-range smartphones. The compression of models by the lightweight 3D asset pipeline is 60 to 70 percent with an almost imperceptible quality loss, with automatic topology optimization and adaptive texture compression. A 200 user study that was conducted using furniture, electronic products and other items revealed that ASE reduces the rate of returns by 25 percent and also 40 percent more session time than a control e-commerce web site. Validation is done with the deployed prototype. Contributions: (1) a complete web-based AR platform to integrate e-commerce, (2) an ideal 3D asset conversion pipeline, (3) a hybrid tracking abstraction layer and (4) empirical performance benchmarks providing practical guidelines to AR implementation in mobile settings with limited resources. Keywords: Customer Experience, Digital Transformation, E-commerce, Immersive Systems, Mixed Reality, WebXR.

The study examines digital transformation's effects on Tamil Nadu's retail and manufacturing sectors by incorporating digital technologies into operations. It compares traditional methods with digital approaches to assess impacts on profitability, customer retention, and efficiency. Data was collected from three retail and two manufacturing firms using a structured questionnaire with 50 respondents. Both quantitative and qualitative analyses were conducted to assess changes in sales, inventory, and customer interaction. Traditional retailers saw a 20.8% drop in growth and profitability due to online shopping, which changed customer behavior and reduced store visits. Customer retention rates fell from 85% to 70%, highlighting the need for improved engagement strategies. Manufacturing firms gained from digital transformation through enhanced efficiency and supply chain management, though they faced challenges such as resistance to change. The findings indicate that traditional retailers must adopt digital marketing, hybrid models, and training to address resistance and skill shortages. Manufacturing companies should continue improving digital capabilities to enhance production and stay competitive in a changing market. The study concludes that while digital transformation poses challenges like reduced retail profitability, it also provides opportunities for efficiency and market growth in both sectors. These insights guide companies and policymakers toward a strategic approach to digitalization for sustainable growth and competitive advantage.

ABSTRACT Consumer trust has emerged as a central construct shaping contemporary apparel shopping behaviour across online and offline channels. This paper presents a systematic conceptual review that synthesizes extant empirical and theoretical findings on trust antecedents, mechanisms, and consequences in the apparel retail context, with emphasis on comparative dynamics between e-commerce and brick-and-mortar settings. Drawing exclusively on the set of studies provided, the review identifies recurring trust dimensions (competence, benevolence, integrity), channel-specific antecedents (website quality, payment security, customer service, tangibility), and mediating constructs (perceived risk, satisfaction, perceived value). It highlights how online apparel shopping relies heavily on transactional cues such as payment security, ease of payment, reviews, and return policies, whereas offline apparel shopping is more strongly influenced by tactile assurance, store ambience, and in-store service quality. The review proposes an integrative conceptual framework linking trust dimensions to perceived risk and channel preference, identifies key moderators (digital literacy, age, gender, financial inclusion), and formulates a research agenda with testable hypotheses for future empirical work. Managerial and policy implications address channel-specific trust interventions: improving website and payment security, optimizing return and review mechanisms, enhancing tangibility and in-store data security, and fostering financial inclusion. Keywords: Omni-channel, consumer trust, apparel shopping, online vs offline.

The store is a component of a bigger brand service chain that takes orders and delivers the things consumers want in person. The online store's manager cares deeply about both the smooth operation of the business and the happiness of its customers. Keeping the firm running, compiling records, and knowing the revenue from online purchasing is the most difficult portion of business making. The convenience of being able to keep track of purchases and take orders over the phone is, hence, the central focus of this research. Customers are given significant prominence in this report through the provision of discounts that are derived from their purchasing history. Consequently, the customer's value to the organisation grows in direct proportion to their level of engagement. This program's limited features, such as product reports, allowed it to partially manage product orders placed on a wide scale online, and it performed admirably across a variety of products. Customers can experience easy product ordering from any location if brand shopping offers an online portal.

Due to quick technological progress and new demands from buyers, the global retail industry is changing rapidly. Shopping, which used to be only in stores, has now changed to mostly being done online and tailored to each person. The paper looks at how retail is being transformed as digital and physical ways of shopping come together due to advances in technology and what customers want. The primary aim of this paper is to explore how technology is redefining the retail landscape. Even though online shopping is convenient and flexible, going to a store gives a unique experience and emotional connection. Recent studies and industry trends are analysed to see how both formats compare in terms of strategy and how omnichannel retail is becoming the main model. Artificial intelligence, mobile platforms, augmented reality, and immersive environments are assessed to see how they influence customers, their loyalty, and the company’s ability to respond quickly. The paper also looks at ethical and management issues, pointing out that balancing innovation with trust, privacy, and inclusivity is very important. It appears that the future of retail will involve using digital tools while maintaining the originality of physical stores, making it possible for retailers to adapt to what consumers want. Practitioners should understand that to succeed in the future, businesses need to concentrate on forming adaptable, inclusive, and experience-centred retail environments.

The Philippine clothing industry is undergoing a rapid shift toward digital transformation; however, small and medium-sized enterprises (SMEs) face challenges in sustaining their competitiveness. This study examines how value creation, value delivery, and value capture shape digital retail performance, addressing gaps in empirical evidence for emerging markets. The study employed a descriptive–correlational design and quantitative analysis, surveying 94 purposively selected SME respondents in Metro Manila. Data were analyzed using multiple regression and mediation–moderation tests. The theoretical framework integrates Service-Dominant Logic, Value Chain Theory, and Transaction Cost Economics to explain the dynamics of digital business models. Findings reveal that value creation, value delivery, and value capture each have significant positive effects on digital retail performance. Mediation analysis highlights the role of customer satisfaction, loyalty, and perceived quality, while moderation analysis confirms the influence of firm size, capitalization, and technological readiness. The results validate a contextualized Digital Retail Business Model tailored to the Philippine clothing sector. The study contributes to business model innovation literature by providing empirical evidence from a developing economy. Practically, it provides SMEs and policymakers with actionable insights for strengthening digital competitiveness, enhancing customer engagement, and promoting inclusive industry growth.

This study aims to analyze the effect of using QRIS and digital promotion on increasing sales at Trendz Store Rantauprapat, a modern clothing store that actively adopts technology in its business operations. The method used is descriptive with a quantitative approach through observation, interviews, and sales data before and after the implementation of QRIS and digital promotions. The results show that the use of QRIS facilitates transactions and increases customer convenience, while digital promotions through social media are effective in attracting new consumers and increasing the loyalty of existing customers. The synergy between the two has a significant impact on increasing sales of Trendz Rantauprapat stores with a joint effect of 40.3%. Therefore, the integration of digital payment technology and online marketing strategies is an important factor in the development of retail businesses in today's digital era.

This study investigates how experiences generated in digital environments – specifically perceived personalization and brand sensory experience – impact the experiential value of physical in-store interactions within the fashion industry. Additionally, it examines the extent to which consumer sensory orientation modulates these effects in omnichannel contexts. A quantitative research design was employed, structured around an experiment combining a simulated digital shopping journey, in-person exposure, and the administration of a standardized questionnaire. The sample, consisting of 445 participants, was recruited through Prolific. Data were analyzed using exploratory and confirmatory factor analyses (EFA and CFA), hierarchical regression models, and interaction tests with bootstrapping, ensuring psychometric robustness and external validity. The results reveal that digital personalization, when lacking coherent sensory alignment, may diminish the perceived value of the in-store experience. Conversely, the online brand sensory experience significantly enhances such valuation. Furthermore, consumers with high sensory orientation amplify these effects: they exhibit greater positive responsiveness to sensory stimuli and lower receptivity to personalizations perceived as generic or intrusive. The primary contribution of this study lies in integrating, within a single explanatory model, the effects of digital experiences on physical evaluations through a sensory and personalized lens. By introducing consumer sensory orientation as a moderating variable, this research advances understanding of omnichannel behavior and offers a more nuanced perspective on the design of effective hybrid experiences in the retail sector. It provides both theoretical insights and managerial implications in a landscape increasingly shaped by technological convergence.

With the fast development of IoT technologies and the potential of real-time data gathering, allowing decision makers to take advantage of real-time visibility on their processes, the rise of Digital Twins (DT) has attracted several research interests. DT are among the highest technological trends for the near future and their evolution is expected to transform the face of several industries and applications and opens the door to a huge number of possibilities. However, DT concept application remains at a cradle stage and it is mainly restricted to the manufacturing sector. In fact, its true potential will be revealed in many other sectors. In this research paper, we aim to propose a DT prototype for instore daily operations management and test its impact on daily operations management performances. More specifically, for this specific research work, we focus the impact analysis of DT in the fitting rooms’ area.

Personal services can be found in sectors such as education, retail, hospitality, and craftsmanship. As of today, personal service firms lack the know-how and experience on how to implement processes and practices to effectively build digital business ecosystems. This becomes an obstacle for these kinds of firms to overcome the challenges of todays digital age. Based on the guidelines of Design Science Research (DSR), we address this gap by proposing a maturity model, which offers specific guidance for this sector to be able to achieve the transition from analog to digital. The design of the model is grounded in a systematic literature review, semi-structured interviews, and a validation test involving company representatives from the field of personal services, business ecosystems, and digitalization. Results revealed a series of dimensions, capabilities, and maturity stages indicating an evolutionary path towards digital maturity for personal service firms. Thus, leading them to achieve a digital business ecosystem.

The quick growth of shops using artificial intelligence (AI) techniques has changed digital marketing activities and changed how businesses interact and reach their consumers. (AI) techniques are reshaping digital interactions between shops and consumers interact digitally by providing a more efficient and customized experience, fostering deeper engagement and more informed decision-making. This study investigates how (AI) techniques affect consumer interaction and decision-making over purchases with shops that use digital marketing. The partial least squares method was used to evaluate data from a survey with 300 respondents. When consumer engagement mediates this relationship, artificial intelligence (AI) techniques have a more favorable impact on purchasing decision-making. Consequently, decision-making is positively impacted through consumer engagement. The findings emphasize that for a bigger impact of the (AI) techniques on decision-making, the consumer must initially interact with the (AI) techniques. This research unveils a contemporary pathway in the field of AI-supported shop engagements and illustrates the distinct impact of (AI) techniques on consumer satisfaction, trust, and loyalty, revolutionizing traditional models of customer-purchase decision-making and shop engagement processes. This study provides previously unheard-of insight, into the revolutionary potential of (AI) techniques in influencing customer behavior and shop relationships

In the era of digital transformation, new technological foundations and possibilities for collaboration, production as well as organization open up many opportunities to work differently in the future. The digitization of workflows results in new forms of working which is denoted by the term Work 4.0. In the context of Work 4.0, digital assistance systems play an important role as they give users additional situation-specific information about a workflow or a product via displays, mobile devices such as tablets and smartphones, or data glasses. Furthermore, such digital assistance systems can be used to provide instructions and technical support in the working process as well as for training purposes. However, existing digital assistance systems are mostly created focusing on the "design for all" paradigm neglecting the situation-specific tasks, skills, preferences, or environments of an individual human worker. To overcome this issue, we present a monitoring and adaptation framework for supporting self-adaptive digital assistance systems for Work 4.0. Our framework supports context monitoring as well as UI adaptation for augmented (AR) and virtual reality (VR)-based digital assistance systems. The benefit of our framework is shown based on exemplary case studies from different domains, e.g. context-aware maintenance application in AR or warehouse management training in VR.

Even though, digital transformation has attracted much attention of both academics and practitioners, a very limited number of studies have investigated the digital transformation process in small and medium-sized enterprises (SMEs) and the findings remain fragmented. Given the accessibility and availability of digital technologies to launch digital transformation initiatives and the importance of SMEs in the economy, a profound understanding of enablers of the digital transformation process in SMEs is much needed. As such, to address this, in this paper we conducted a comprehensive review of related literature in information systems, management, and business disciplines, to identify key enablers that facilitate the digital transformation process in SMEs.

Multimodal foundation models have demonstrated strong generalization, yet their ability to transfer knowledge to specialized domains such as garment generation remains underexplored. We introduce VLG, a vision-language-garment model that synthesizes garments from textual descriptions and visual imagery. Our experiments assess VLG's zero-shot generalization, investigating its ability to transfer web-scale reasoning to unseen garment styles and prompts. Preliminary results indicate promising transfer capabilities, highlighting the potential for multimodal foundation models to adapt effectively to specialized domains like fashion design.

We introduce GarmentCrafter, a new approach that enables non-professional users to create and modify 3D garments from a single-view image. While recent advances in image generation have facilitated 2D garment design, creating and editing 3D garments remains challenging for non-professional users. Existing methods for single-view 3D reconstruction often rely on pre-trained generative models to synthesize novel views conditioning on the reference image and camera pose, yet they lack cross-view consistency, failing to capture the internal relationships across different views. In this paper, we tackle this challenge through progressive depth prediction and image warping to approximate novel views. Subsequently, we train a multi-view diffusion model to complete occluded and unknown clothing regions, informed by the evolving camera pose. By jointly inferring RGB and depth, GarmentCrafter enforces inter-view coherence and reconstructs precise geometries and fine details. Extensive experiments demonstrate that our method achieves superior visual fidelity and inter-view coherence compared to state-of-the-art single-view 3D garment reconstruction methods.

Nowadays social media (Twitter, Facebook, etc.), not only simply as communication media, but also for promotion. Social networking media offers many business benefits for companies and organizations. Research purposes is to determine the model of social network media utilization as a promotional media for handicraft business in Palembang city. Qualitative and quantitative research design are used to know how handicraft business in Palembang city utilizing social media networking as a promotional media. The research results show 35% craft businesses already utilizing social media as a promotional media. The social media used are blog development 15%, facebook 46%, and twitter etc. are 39%. The reasons they use social media such as, 1) minimal cost, 2) easily recognizable, 3) global distribution areas. Social media emphasis on direct engagement with customers better. So that the marketing method could be more personal through direct communication with customers.

The handicraft industry is a strong pillar of Indian economy which provides large-scale employment opportunities to artisans in rural and underprivileged communities. However, in this era of globalization, diverse modern designs have rendered traditional designs old and monotonous, causing an alarming decline of handicraft sales. For this age-old industry to survive the global competition, it is imperative to integrate contemporary designs with Indian handicrafts. In this paper, we use novel AI techniques to generate contemporary designs for two popular Indian handicrafts - Ikat and Block Print. These techniques were successfully employed by communities across India to manufacture and sell products with greater appeal and revenue. The designs are evaluated to be significantly more likeable and marketable than the current designs used by artisans.

The introduction of cloud computing has provided opportunities for small businesses to implement enterprise systems (ES) in their organizations and thereby improve their business processes. While there have been many studies focusing on ES implementation among medium-large sized firms, the factors that influence the implementations of ES in such firms are different to that of small firms. This teaching case discusses an implementation of a cloud enterprise resource planning (ERP) system in a small firm in the Asian region. The case illustrates factors that enabled successful implementation of a cloud ERP system in a small firm and the lessons learnt through this successful endeavor. The case study and the teaching notes are suitable for any undergraduate or postgraduate cohort, following a course in management information systems.

We extend the model of Parenti (2018) on large and small firms by introducing cost heterogeneity among small firms. We propose a novel necessary and sufficient condition for the existence of such a mixed market structure. Furthermore, in contrast to Parenti (2018), we show that in the presence of cost heterogeneity among small firms, trade liberalization may raise or reduce the mass of small firms in operation.

The emergence of breakthrough artificial intelligence (AI) techniques has led to a renewed focus on how small data settings, i.e., settings with limited information, can benefit from such developments. This includes societal issues such as how best to include under-represented groups in data-driven policy and decision making, or the health benefits of assistive technologies such as wearables. We provide a conceptual overview, in particular contrasting small data with big data, and identify common themes from exemplary case studies and application areas. Potential solutions are described in a more detailed technical overview of current data analysis and modelling techniques, highlighting contributions from different disciplines, such as knowledge-driven modelling from statistics and data-driven modelling from computer science. By linking application settings, conceptual contributions and specific techniques, we highlight what is already feasible and suggest what an agenda for fully leveraging small data might look like.

Future fully interconnected virtual reality (VR) systems and the Tactile Internet diminish the boundary between virtual (online) and real (offline) worlds, while extending the digital and physical capabilities of humans via edge computing and teleoperated robots, respectively. In this paper, we focus on the Internet of No Things as an extension of immersive VR from virtual to real environments, where human-intended Internet services - either digital or physical - appear when needed and disappear when not needed. We first introduce the concept of integrated online-to-offline (O2O) communications, which treats online and offline channels as complementary to bridge the virtual and physical worlds and provide O2O multichannel experiences. We then elaborate on the emerging extended reality (XR), which brings the different forms of virtual/augmented/mixed reality together to realize the entire reality-virtuality continuum and, more importantly, supports human-machine interaction as envisioned by the Tactile Internet, while posing challenges to conventional handhelds, e.g., smartphones. Building on the so-called invisible-to-visible (I2V) technology concept, we present our extrasensory perception network (ESPN) and investigate how O2O communications and XR can be combined for the nonlocal extension of human "sixth-sense" experiences in space and time. We conclude by putting our ideas in perspective of the 6G vision.

This demo showcases a simple tool that utilizes AIGC technology, enabling both professional designers and regular users to easily customize clothing for their digital avatars. Customization options include changing clothing colors, textures, logos, and patterns. Compared with traditional 3D modeling processes, our approach significantly enhances efficiency and interactivity and reduces production costs.

The paper is devoted to the realization of wireless enabled clothing, employing recent new technologies in electronics, textile, and renewable power. This new wireless enabled clothing architecture is modular and distributed,allowing for customization in functionality and clothing designs. Are studied the implications for supply chains,distribution channels, and cost benefits. Modular wireless enabled clothing offers significant personalization opportunities at costs comparable with mobile terminals.

With the increasing development of garment manufacturing industry, the method of combining neural network with industry to reduce product redundancy has been paid more and more attention.In order to reduce garment redundancy and achieve personalized customization, more researchers have appeared in the field of virtual trying on.They try to transfer the target clothing to the reference figure, and then stylize the clothes to meet user's requirements for fashion.But the biggest problem of virtual try on is that the shape and motion blocking distort the clothes, causing the patterns and texture on the clothes to be impossible to restore. This paper proposed a new stylized virtual try on network, which can not only retain the authenticity of clothing texture and pattern, but also obtain the undifferentiated stylized try on. The network is divided into three sub-networks, the first is the user image, the front of the target clothing image, the semantic segmentation image and the posture heat map to generate a more detailed human parsing map. Second, UV position map and dense correspondence are used to map patterns and textures to the deformed silhouettes in real time, so that they can be retained in real time, and the rationality of spatial structure can be guaranteed on the basis of improving the authenticity of images. Third,Stylize and adjust the generated virtual try on image. Through the most subtle changes, users can choose the texture, color and style of clothing to improve the user's experience.

Mass customization explains the phenomenon to provide a unique designed products and services to all customer by achieving a high process integration and flexibility. It has been used as a competitive approach by many companies. Adequate resource implementation in mass customization-particularly in terms of resource usage, it is therefore important to meet customer's requirement in terms effective responsiveness and meeting deadlines, at the same time offering high scalability. An architecture for solving the resource allocation issue in mass customized flexible manufacturing system was illustrated, by putting in place a couple of advance reservation systems and scheduling algorithms for effective usage of the product.

The hierarchical structure of production planning has the advantage of assigning different decision variables to their respective time horizons and therefore ensures their manageability. However, the restrictive structure of this top-down approach implying that upper level decisions are the constraints for lower level decisions also has its shortcomings. One problem that occurs is that deterministic mixed integer decision problems are often used for long-term planning, but the real production system faces a set of stochastic influences. Therefore, a planned utilisation factor has to be included into this deterministic aggregate planning problem. In practice, this decision is often based on past data and not consciously taken. In this paper, the effect of long-term forecast error on the optimal planned utilisation factor is evaluated for a production system facing stochastic demand and the benefit of exploiting this decision's potential is discussed. Overall costs including capacity, backorder and inventory costs, are determined with simulation for different multi-stage and multi-item production system structures. The results show that the planned utilisation factor used in the aggregate planning problem has a high influence on optimal costs. Additionally, the negative effect of forecast errors is evaluated and discussed in detail for different production system environments.

Manufacturing companies face challenges when it comes to quickly adapting their production control to fluctuating demands or changing requirements. Control approaches that encapsulate production functions as services have shown to be promising in order to increase the flexibility of Cyber-Physical Production Systems. But an existing challenge of such approaches is finding a production plan based on provided functionalities for a demanded product, especially when there is no direct (i.e., syntactic) match between demanded and provided functions. While there is a variety of approaches to production planning, flexible production poses specific requirements that are not covered by existing research. In this contribution, we first capture these requirements for flexible production environments. Afterwards, an overview of current Artificial Intelligence approaches that can be utilized in order to overcome the aforementioned challenges is given. For this purpose, we focus on planning algorithms, but also consider models of production systems that can act as inputs to these algorithms. Approaches from both symbolic AI planning as well as approaches based on Machine Learning are discussed and eventually compared against the requirements. Based on this comparison, a research agenda is derived.

Digital Engineering, the digital transformation of engineering to leverage digital technologies, is coming globally. This paper explores digital systems engineering, which aims at developing theory, methods, models, and tools to support the emerging digital engineering. A critical task is to digitalize engineering artifacts, thus enabling information sharing across platform, across life cycle, and across domains. We identify significant challenges and enabling digital technologies; analyze the transition from traditional engineering to digital engineering; define core concepts, including "digitalization", "unique identification", "digitalized artifacts", "digital augmentation", and others; present a big picture of digital systems engineering in four levels: vision, strategy, action, and foundation; briefly discuss each of main areas of research issues. Digitalization enables fast infusing and leveraging novel digital technologies; unique identification enables information traceability and accountability in engineering lifecycle; provenance enables tracing dependency relations among engineering artifacts; supporting model reproducibility and replicability; helping with trustworthiness evaluation of digital engineering artifacts.

To meet order fulfillment targets, manufacturers seek to optimize production schedules. Machine learning can support this objective by predicting throughput times on production lines given order specifications. However, this is challenging when manufacturers produce customized products because customization often leads to changes in the probability distribution of operational data -- so-called distributional shifts. Distributional shifts can harm the performance of predictive models when deployed to future customer orders with new specifications. The literature provides limited advice on how such distributional shifts can be addressed in operations management. Here, we propose a data-driven approach based on adversarial learning and job shop scheduling, which allows us to account for distributional shifts in manufacturing settings with high degrees of product customization. We empirically validate our proposed approach using real-world data from a job shop production that supplies large metal components to an oil platform construction yard. Across an extensive series of numerical experiments, we find that our adversarial learning approach outperforms common baselines. Overall, this paper shows how production managers can improve their decision-making under distributional shifts.

In this paper, we extend the model of Gao and Su (2016) and consider an omnichannel strategy in which inventory can be replenished when a retailer sells only in physical stores. With "buy-online-and-pick-up-in-store" (BOPS) having been introduced, consumers can choose to buy directly online, buy from a retailer using BOPS, or go directly to a store to make purchases without using BOPS. The retailer is able to select the inventory level to maximize the probability of inventory availability at the store. Furthermore, the retailer can incur an additional cost to reduce the BOPS ordering lead time, which results in a lowered hassle cost for consumers who use BOPS. In conclusion, we found that there are two types of equilibrium: that in which all consumers go directly to the store without using BOPS and that in which all consumers use BOPS.

Women who have undergone mastectomy and do not undergo reconstruction often face challenges with existing bras and prostheses. Mismatches between generic prostheses and individual mastectomy cases result in physical and mental discomfort, such as pain, sweating, asymmetry, and concerns about prosthesis movement. Existing solutions are limited in their ability to address these challenges effectively. This study aims to develop a workflow for designing and fabricating a lightweight post-mastectomy bra with an incorporated prosthesis to improve fit, symmetry, and comfort. We developed a customization and fabrication workflow based on a three-dimensional (3D) scan and the manipulation of its geometry to achieve fit and symmetry. We leverage the 3D-printed spacer fabric technique to produce a lightweight, breathable structure. We conducted mechanical tests to determine printing parameters and evaluate the compression properties of the prosthesis and the bra materials. Additionally, we conducted a wear test for 10 women who underwent a mastectomy. A personalized bra was printed for each, and their feedback on fit and comfort was collected weekly over a 3-week test period. The printed bras were lightweight (150-250 g), breathable, and provided improved symmetry. The mechanical tests confirmed comparable softness to silicone prostheses at significantly lower weight. The user study results show that the custom bras offer several advantages, including reduced weight and improved symmetry, though some participants noted mild fit and texture issues. Integrating the prosthesis into a 3D-printed bra offers a promising personalized solution for post-mastectomy women. This approach enhances comfort, symmetry, and emotional well-being, however, further improvements need to be made to improve the material and tactility. Many women who undergo a mastectomy are unable to have breast reconstruction for various reasons. These women usually choose to wear a silicone prosthesis placed in a special bra. This solution often exacerbates physical and mental discomfort due to a mismatch between the bra and the body. Women often suffer from excessive sweating, rashes, pressure, and shoulder pain from the prosthesis’s weight. In addition, there are issues of asymmetry, and they often fear that the prosthesis might move or fall, making them feel uncomfortable and embarrassed. The paper addresses these challenges by introducing a novel approach in which a prosthesis is incorporated into a 3D-printed, custom-fitted bra. Each bra is meticulously customized to the unique anatomy of the post-mastectomy woman, utilizing 3D scanning technology to precisely capture body contours. This data is then processed and refined to generate a digital blueprint, enabling the production of a bespoke bra tailored to the individual’s needs. Leveraging advanced 3D Printed Spacer Fabrics (3DSF) technology enables the creation of a breathable, lightweight bra that is up to 30% lighter than a silicone prosthesis. We use two scans, one with a bra and one without, to design the prosthetic shape in order to achieve a symmetrical appearance. This study was an evaluation by a user study that included 10 women who wore the bra for a few hours a day over a period of three weeks. The participants provided feedback on the fit, comfort, and self-perception of femininity. The results show that most women are happy with the weight reduction and report a decrease in sweating, while feedback on fit and overall satisfaction varies. We hope that this research will raise awareness and encourage further exploration to improve the lives of mastectomy survivors.

Aquaponics is a green and efficient agricultural production model that combines aquaculture and vegetable cultivation. It is worth looking into optimizing the proportion of fish and plants to improve the quality and yield. However, there is little non-destructive monitoring of plant growth in aquaponics monitoring systems currently. In this paper, based on the Internet of Things technologies, a monitoring system is designed with miniaturization, modularization, and low-cost features for cultivation-breeding ratio research. The system can realize remote monitoring and intelligent control of parameters needed to keep fish and plants under optimal conditions. First, a 32-bit chip is used as the Microcontroller Unit to develop the intelligent sensing unit, which can realize 16 different data acquisitions as stand-alone extensible modules. Second, to achieve plant data acquisition and upload, the Raspberry Pi embedded with image processing algorithms is introduced to realize edge-computing. Finally, all the collected data is stored in the Ali-cloud through Wi-Fi and a WeChat Mini Program is designed to display data and control devices. The results show that there is no packet loss within 90 m for wireless transmission, and the error rate of environment parameters is limited to 5%. It was proven that the system is intelligent, flexible, low-cost, and stable which is suitable for small-scale aquaponics well.

This paper provides a novel methodology for human-driven decision support for capacity allocation in labour-intensive manufacturing systems. In such systems (where output depends solely on human labour) it is essential that any changes aimed at improving productivity are informed by the workers' actual working practices, rather than attempting to implement strategies based on an idealised representation of a theoretical production process. This paper reports how worker position data (obtained by localisation sensors) can be used as input to process mining algorithms to generate a data-driven process model to understand how manufacturing tasks are actually performed and how this model can then be used to build a discrete event simulation to investigate the performance of capacity allocation adjustments made to the original working practice observed in the data. The proposed methodology is demonstrated using a real-world dataset generated by a manual assembly line involving six workers performing six manufacturing tasks. It is found that, with small capacity adjustments, one can reduce the completion time by 7% (i.e., without requiring any additional workers), and with an additional worker a 16% reduction in completion time can be achieved by increasing the capacity of the bottleneck tasks which take relatively longer time than others.

In the 21st century's digital age, health organizations face challenges from reduced public healthcare spending, creating a competitive market that impacts healthcare management. The struggle is hardest for small organizations, such as private clinics. Competing under unfavorable conditions, these small businesses must run as independent, profitable units in a government-regulated market where they are subject to numerous restrictions yet receive no financial support. In a world of increasing dependence on digital technologies, these small businesses must adopt competitive business models and be adaptive and flexible in embracing change. This qualitative study is based on a thematic qualitative analysis of 20 in-depth, 45-minute-long interviews with dentists and owners of private dental clinics in various specialties. The study employs the strategic change model to examine how dentists who run private dental clinics implement new strategies and technologies to adjust to changes and create a competitive edge. Six main categories emerged from the analysis of the interviews: changes in the organization's environment; instituting and assimilating changes; obstacles in embracing change; added value obtained from embracing the change; quality of care and service; and cost-benefit considerations. The categories were map and evaluated in light of the strategic change model. The analysis indicated that digital strategies have been only partially adopted, suggesting an absence of a cohesive, long-term strategic vision for the organizations. The study explored the actions, perceptions, and challenges of adapting to a competitive digital market in dental private clinics. Based on these insights, recommendations have been provided for global change management, aiming for a sustainable and stable healthcare system that benefits the broader community.

Many small businesses and startups struggle to adjust their operational plans to quickly changing market and financial situations. Traditional data-driven techniques often miss possibilities and waste resources. Our unique approach, Unified Statistical Association Validation (USAV), allows dynamic and real-time data association and improvement assessment to address this essential issue. USAV classifies and validates critical data associations based on business features to improve startup incubation and innovation decision-making. USAV analyses different financial eras using federated learning to find performance inefficiencies using a Kaggle dataset on small business success and failure. USAV recommends actionable improvements during innovation using non-recurrent statistical patterns, unlike standard models that use prior financial data. The framework allows real-time flexibility with continual statistical updates without data redundancy. The proposed approach achieved an improvement assessment score of 0.98, data association accuracy of 96%, statistical update efficiency of 0.97, modification ratio of 35%, and incubation analysis time reduction of 240 units in experimental evaluation. These findings demonstrate USAV's ability to help strategic decision-making in dynamic corporate situations.

In the 1980s, companies discovered time as a new source of competitive advantage. In the 1990s, they will discover that time is only one piece of a more far-reaching transformation in the logic of competition. Using examples from Wal-Mart and other highly successful companies, Stalk, Evans, and Shulman of the Boston Consulting Group provide managers with a guide to the new world of "capabilities-based competition." In today's dynamic business environment, strategy too must become dynamic. Competition is a "war of movement" in which success depends on anticipation of market trends and quick response to changing customer needs. In such an environment, the essence of strategy is not the structure of a company's products and markets but the dynamics of its behavior. To succeed, a company must weave its key business processes into hard-to-imitate strategic capabilities that distinguish it from its competitors in the eyes of customers. A capability is a set of business processes strategically understood--for example, Wal-Mart's expertise in inventory replenishment, Honda's skill at dealer management, or Banc One's ability to "out-local the national banks and out-national the local banks." Such capabilities are collective and cross-functional--a small part of many people's jobs, not a large part of a few. Finally, competing on capabilities requires strategic investments in support systems that span traditional SBUs and functions and go far beyond what traditional cost-benefit metrics can justify. A CEO's success in building and managing a company's capabilities will be the chief test of management skill in the 1990s. The prize: companies that combine scale and flexibility to outperform the competition.

Competition on the Internet is creating fierce battles between industry giants and small-scale start-ups. Smart start-ups can avoid those conflicts by moving quickly to uncontested ground and, when that's no longer possible, turning dominant players' strengths against them. The authors call this competitive approach judo strategy. They use the Netscape-Microsoft battles to illustrate the three main principles of judo strategy: rapid movement, flexibility, and leverage. In the early part of the browser wars, for instance, Netscape applied the principle of rapid movement by being the first company to offer a free stand-alone browser. This allowed Netscape to build market share fast and to set the market standard. Flexibility became a critical factor later in the browser wars. In December 1995, when Microsoft announced that it would "embrace and extend" competitors' Internet successes, Netscape failed to give way in the face of superior strength. Instead it squared off against Microsoft and even turned down numerous opportunities to craft deep partnerships with other companies. The result was that Netscape lost deal after deal when competing with Microsoft for common distribution channels. Netscape applied the principle of leverage by using Microsoft's strengths against it. Taking advantage of Microsoft's determination to convert the world to Windows or Windows NT, Netscape made its software compatible with existing UNIX systems. While it is true that these principles can't replace basic execution, say the authors, without speed, flexibility, and leverage, very few companies can compete successfully on Internet time.