The feasibility of adopting clothing mass customisation in South Africa

Abstract: Mass Customisation (MC) is increasingly seen as a strategy to survive in the competitive clothing fashion markets. This importance to retail sales necessitates its consideration in the South African context. There is a paucity of literature on adopting MC so exploring the feasibility of MC for South African clothing manufacturers was a step in understanding what is required from manufacturers. Three corporate clothing manufacturers were selected for qualitative interviews to determine whether they currently exhibit identified competencies from literature considered essential to undertake MC. Two manufacturers exhibited key competencies of communication, human capital, flexibility and technology needed for MC success

Eine Analyse der Literatur zur Referenzmodellierung im Geschäftsprozessmanagement unter Berücksichtigung quantitativer Methoden

Im Geschäftsprozessmanagement nimmt die Referenzmodellierung bei der Gestaltung von Geschäftsprozessen eine große Bedeutung ein, da auf bereits existierende Modelle zurückgegriffen werden kann. So kann Zeit für die Entwicklung der Prozesse eingespart und von bereits etabliertem Wissen profitiert werden. Die vorliegende Masterarbeit analysiert die Literatur im Bereich der Referenzmodellierung im Geschäftsprozessmanagement unter Berücksichtigung quantitativer Methoden. Es werden insbesondere die Forschungsrichtungen bzw. Themenbereiche, Entwicklungen und der aktuelle Stand der Literatur in diesem Bereich ermittelt. Zunächst werden deutsch- und englischsprachige Artikel nach bestimmten Kriterien ausgewählt. Anschließend folgt eine quantitativ orientierte Analyse der Literatur. Dabei kommt die Latente Semantische Analyse zum Einsatz, mit deren Hilfe Themenbereiche ermittelt werden und die einzelnen Beiträge den ermittelten Themenbereichen zugeordnet werden können. Darüber hinaus wird die Entwicklung der Anzahl der Artikel in den Themenbereichen im Zeitverlauf betrachtet und auf Unterschiede zwischen der deutsch- und englischsprachigen Literatur eingegangen. In der darauf folgenden qualitativ orientierten Analyse werden die Artikel der einzelnen Themenbereiche inhaltlich analysiert und der aktuelle Stand der Forschung dargestellt. Nicht zuletzt werden die Ergebnisse der qualitativen Analyse in Bezug zu den Ergebnissen der quantitativen Analyse gesetzt

The impact of supply chain structures on performance.

La Tesis analiza el impacto que tiene la estructura de las redes de suministro sobre su rendimiento, concretamente sobre el “efecto látigo” o efecto bullwhip. Para ello se desarrolla una arquitectura basada en la metodología de los sistemas multi-agente, que permite el modelado de sistemas complejos. Dicha arquitectura es implementada en un software dando lugar a un simulador de redes de suministro llamado SCOPE, que permite el modelado y simulación de una amplia variedad de configuraciones de redes de suministro. SCOPE es utilizado para investigar una de las suposiciones más comunes en el campo del modelado de redes de suministro: el uso de estructuras muy sencillas en forma serial generalmente con muy pocas fases funcionales y pocos nodos. Para determinar el impacto de la estructura de la red sobre el efecto bullwhip se utiliza una estructura más compleja y más acorde con las estructuras de redes de suministro reales: la red divergente. Se realizan tres experimentos: (i) análisis comparativo del efecto bullwhip entre la red divergente y la serial; (ii) análisis comparativo de la eficacia de dos técnicas muy conocidas para la limitación del efecto bullwhip entre la red divergente y la serial; (iii) determinación de los parámetros estructurales de la red de suministro divergente y análisis estadístico para determinar si dichos parámetros estructurales impactan sobre el efecto bullwhip. Los resultados obtenidos revelan que todos los parámetros estructurales analizados impactan significativamente sobre efecto bullwhip. Además, en caso de un impulso inesperado en la demanda, el impacto de la red de suministro en el efecto bullwhip es mayor. Las técnicas para limitación del efecto bullwhip son también efectivas en redes de suministro divergentes, consiguiendo además un aumento de su robustez ante cambios bruscos inesperados en la demanda

Advanced technologies and international business : A multidisciplinary analysis of the literature

Publisher Copyright: © 2021 The AuthorsAdvanced digital technologies, such as the Internet of Things, blockchain, big data analytics and augmented reality, are gradually transforming the way multinational firms do business. Due to the extent of this transformation many scholars argue that the integration of these technologies marks the commencement of the fourth industrial revolution (Industry 4.0). However, the question how these advanced technologies impact international business activities needs further attention. To this end, we adopt a multidisciplinary approach to review the related literature in international business (IB), general management, information systems, and operations research. We include the two latter fields, because advanced technologies have received more attention in these bodies of literature. Based on our analysis, we discuss the implications of these technologies for international business. Further, we highlight the drivers of technology utilisation by multinational firms and likely outcomes. We also provide future research avenues.Peer reviewe

Big data analytics tools for improving the decision-making process in agrifood supply chain

Introduzione: Nell'interesse di garantire una sicurezza alimentare a lungo termine di fronte a circostanze mutevoli, è necessario comprendere e considerare gli aspetti ambientali, sociali ed economici del processo di produzione. Inoltre, a causa della globalizzazione, sono stati sollevati i problemi delle lunghe filiere agroalimentari, l'asimmetria informativa, la contraffazione, la difficoltà di tracciare e rintracciare l'origine dei prodotti e le numerose questioni correlate quali il benessere dei consumatori e i costi sanitari. Le tecnologie emergenti guidano verso il raggiungimento di nuovi approcci socioeconomici in quanto consentono al governo e ai singoli produttori agricoli di raccogliere ed analizzare una quantità sempre crescente di dati ambientali, agronomici, logistici e danno la possibilità ai consumatori ed alle autorità di controllo della qualità di accedere a tutte le informazioni necessarie in breve tempo e facilmente. Obiettivo: L'oggetto della ricerca riguarda lo studio delle modalità di miglioramento del processo produttivo attraverso la riduzione dell'asimmetria informativa, rendendola disponibile alle parti interessate in un tempo ragionevole, analizzando i dati sui processi produttivi, considerando l'impatto ambientale della produzione in termini di ecologia, economia, sicurezza alimentare e qualità di cibo, costruendo delle opportunità per le parti interessate nel prendere decisioni informate, oltre che semplificare il controllo della qualità, della contraffazione e delle frodi. Pertanto, l'obiettivo di questo lavoro è quello di studiare le attuali catene di approvvigionamento, identificare le loro debolezze e necessità, analizzare le tecnologie emergenti, le loro caratteristiche e gli impatti sulle catene di approvvigionamento e fornire utili raccomandazioni all'industria, ai governi e ai policy maker.Introduction: In the interest of ensuring long-term food security and safety in the face of changing circumstances, it is interesting and necessary to understand and to take into consideration the environmental, social and economic aspects of food and beverage production in relation to the consumers’ demand. Besides, due to the globalization, the problems of long supply chains, information asymmetry, counterfeiting, difficulty for tracing and tracking back the origin of the products and numerous related issues have been raised such as consumers’ well-being and healthcare costs. Emerging technologies drive to achieve new socio-economic approaches as they enable government and individual agricultural producers to collect and analyze an ever-increasing amount of environmental, agronomic, logistic data, and they give the possibility to the consumers and quality control authorities to get access to all necessary information in a short notice and easily. Aim: The object of the research essentially concerns the study of the ways for improving the production process through reducing the information asymmetry, making it available for interested parties in a reasonable time, analyzing the data about production processes considering the environmental impact of production in terms of ecology, economy, food safety and food quality and build the opportunity for stakeholders to make informed decisions, as well as simplifying the control of the quality, counterfeiting and fraud. Therefore, the aim of this work is to study current supply chains, to identify their weaknesses and necessities, to investigate the emerging technologies, their characteristics and the impacts on supply chains, and to provide with the useful recommendations the industry, governments and policymakers

Simplexity: A Hybrid Framework for Managing System Complexity

Knowledge management, management of mission critical systems, and complexity management rely on a triangular support connection. Knowledge management provides ways of creating, corroborating, collecting, combining, storing, transferring, and sharing the know-why and know-how for reactively and proactively handling the challenges of mission critical systems. Complexity management, operating on “complexity” as an umbrella term for size, mass, diversity, ambiguity, fuzziness, randomness, risk, change, chaos, instability, and disruption, delivers support to both knowledge and systems management: on the one hand, support for dealing with the complexity of managing knowledge, i.e., furnishing criteria for a common and operationalized terminology, for dealing with mediating and moderating concepts, paradoxes, and controversial validity, and, on the other hand, support for systems managers coping with risks, lack of transparence, ambiguity, fuzziness, pooled and reciprocal interdependencies (e.g., for attaining interoperability), instability (e.g., downtime, oscillations, disruption), and even disasters and catastrophes. This support results from the evident intersection of complexity management and systems management, e.g., in the shape of complex adaptive systems, deploying slack, establishing security standards, and utilizing hybrid concepts (e.g., hybrid clouds, hybrid procedures for project management). The complexity-focused manager of mission critical systems should deploy an ambidextrous strategy of both reducing complexity, e.g., in terms of avoiding risks, and of establishing a potential to handle complexity, i.e., investing in high availability, business continuity, slack, optimal coupling, characteristics of high reliability organizations, and agile systems. This complexity-focused hybrid approach is labeled “simplexity.” It constitutes a blend of complexity reduction and complexity augmentation, relying on the generic logic of hybrids: the strengths of complexity reduction are capable of compensating the weaknesses of complexity augmentation and vice versa. The deficiencies of prevalent simplexity models signal that this blended approach requires a sophisticated architecture. In order to provide a sound base for coping with the meta-complexity of both complexity and its management, this architecture comprises interconnected components, domains, and dimensions as building blocks of simplexity as well as paradigms, patterns, and parameters for managing simplexity. The need for a balanced paradigm for complexity management, capable of overcoming not only the prevalent bias of complexity reduction but also weaknesses of prevalent concepts of simplexity, serves as the starting point of the argumentation in this chapter. To provide a practical guideline to meet this demand, an innovative model of simplexity is conceived. This model creates awareness for differentiating components, dimensions, and domains of complexity management as well as for various species of interconnectedness, such as the aligned upsizing and downsizing of capacities, the relevance of diversity management (e.g., in terms of deviations and errors), and the scope of risk management instruments. Strategies (e.g., heuristics, step-by-step procedures) and tools for managing simplexity-guided projects are outlined

Resilient Digital Supply Chain Twins Modelling: Simulation-based Analysis on the COVID-19 Pandemic Outbreak

Over the past few years, Supply Chains (SC) have expanded rapidly in terms of dimensions and complexity (e.g., globalization, outsourcing, etc.). Besides, numerous practitioners and researchers proposed models mainly focused on minimizing SC’s total cost. Consequently, the potential financial advantages of reduced stock levels and inventory buffers have made SCs more vulnerable to local and global Low-Frequency High-Impact disruption risks which have long-term destructive effects. For instance, the COVID-19 pandemic outbreak has severely disturbed SCs, especially for essential products, by a sharp increase in demand and raw material supply failure. During this challenging situation, the focus should be shifted from cost minimization to SC’s survival, maximizing demand satisfaction, and minimizing delivery time. Consequently, these emerging issues have put forth the need for greater emphasis to develop resilient supply chains. This study presents a methodological SC simulation modelling framework that enables visualizing the SC and making quick decisions by SC managers in near real-time to ensure resiliency during the disruption. The solution approach is applied as a case study in Luxxeen Co., a Canadian manufacturer of green disposable products, i.e. Toilet Tissues, which is considered an essential product. First, we develop SC’s structural and behavioral conceptual model by customizing the SCOR reference model. Afterwards, we translate it to Discrete Event Simulation formalist and implement it using the “Arena simulation software” platform. Next, we design three COVID-19 pandemic outbreak disruption scenarios in suppliers, transportation networks, and retailers. Finally, three risk mitigation strategies (i.e., Multiple Sourcing, Changing Inventory Control Policy and Buffering) are suggested to ensure SC resiliency in terms of reliability and responsiveness performance metrics. Moreover, by conducting a comparison analysis using “Process Analyzer” and “Optquest” between these scenarios, the best set of actions are proposed for each disruption scenario

Évaluation des stratégies à flux tiré et flux poussé dans la production de bois d'œuvre : une approche basée sur des agents

L’objectif de l’étude est d’évaluer des stratégies en flux tiré et flux poussé pour la planification de la production en utilisant comme cas d’étude une usine de sciage située au Québec. Un outil de planification de la production (APS, Advanced Planning and Scheduling System), basé sur une architecture logicielle distribuée, simule les divers processus de production et planification des opérations de la scierie (approvisionnement, sciage, séchage, rabotage, entreposage et distribution) en les représentant comme des agents logiciels spécifiques. Pour les expériences, des configurations de pilotage définies par deux facteurs contrôlables sont utilisées, à savoir : la position du point de découplage et les niveaux des contrats pour une famille de produits. Ensuite, des scénarios ont été définis par deux facteurs non contrôlables : la qualité de l’approvisionnement et le différentiel des prix pour les produits visés par les contrats. Ces configurations et ces scénarios génèrent un plan d’expériences de niveaux mixtes avec cinquante-quatre expériences. Pour chacun des 54 plans de production généré par l’APS trois indicateurs de performance sont calculés : le taux de service, le niveau de stock de produits en-cours et le profit potentiel de la production (Potential Monetary Throughput). Les résultats montrent une relation directe entre le niveau de pénétration du point de découplage, le flux tiré et le taux de service, pour chaque niveau de demande des produits tirés par les contrats. Ainsi, une planification qui incorpore le flux tiré génère en moyenne une augmentation de performance de 100% dans le niveau de service, par rapport à une planification en flux poussé pour tous les niveaux de contrats. Cette augmentation de la performance du niveau de service a un coût financier d’approximativement 7% du profit potentiel, lequel devrait être compensé par de meilleures conditions des contrats (un premium payé sur le prix marché) et des coûts de stockage plus bas. Ce « compromis » s’avère un résultat direct de la divergence dans la production de bois d’œuvre. Ainsi, dans un contexte d’affaires qui privilégie la qualité du service et où les clients sont prêts à payer pour ce service, l’utilisation de ces stratégies de planification de la production, où le point de découplage est situé en amont de la chaîne, est une opportunité possible d’avantage concurrentiel.The objective of this study is the evaluation of pull and push strategies in lumber production planning using a Quebec sawmill as case study. An Advanced Planning and Scheduling System (APS), based on a distributed software architecture, simulates the main operations planning and production processes of the sawmill (sourcing, sawing, drying, finishing, warehousing and delivery) representing them as autonomous software agents. Push and pull strategies are simulated using different penetration positions of the demand information decoupling point over the value chain. To set experiments, configurations are defined by two controllable factors, namely: the decoupling point position and the level of contracts for a product family. Following, a set of scenarios are generated by two uncontrollable factors: the quality of supply and market prices differential for products under contracts. These configurations and scenarios leads to a mixed levels experimental design with fifty four runs. Three performance indicators: orders fill rate, work in process, and potential monetary throughput; are calculated for every one of the 54 production plans generated by the APS. Results show a direct relation between the orders fill rate and the position of the decoupling point, pull strategy, for the three levels of demand on products under contract. Accordingly, at every demand level, production plans under pull strategies generate improvements of 100% compared with equivalent plans under push strategy. This service level performance improvement has a financial cost of about 7% of the Potential Monetary Throughput which should be compensated externally with better contract conditions and internally by lower costs of inventory management. This trade-off seems to be a direct consequence of the divergent nature of lumber production. Consequently, in a business context that privileges service quality and where customers are willing to pay for it, the use of this kind of demand driven strategies in production planning represents a source of competitive advantage

Predicting potential customer needs and wants for agile design and manufacture in an industry 4.0 environment

Manufacturing is currently experiencing a paradigm shift in the way that products are designed, produced and serviced. Such changes are brought about mainly by the extensive use of the Internet and digital technologies. As a result of this shift, a new industrial revolution is emerging, termed “Industry 4.0” (i4), which promises to accommodate mass customisation at a mass production cost. For i4 to become a reality, however, multiple challenges need to be addressed, highlighting the need for design for agile manufacturing and, for this, a framework capable of integrating big data analytics arising from the service end, business informatics through the manufacturing process, and artificial intelligence (AI) for the entire manufacturing value chain. This thesis attempts to address these issues, with a focus on the need for design for agile manufacturing. First, the state of the art in this field of research is reviewed on combining cutting-edge technologies in digital manufacturing with big data analysed to support agile manufacturing. Then, the work is focused on developing an AI-based framework to address one of the customisation issues in smart design and agile manufacturing, that is, prediction of potential customer needs and wants. With this framework, an AI-based approach is developed to predict design attributes that would help manufacturers to decide the best virtual designs to meet emerging customer needs and wants predictively. In particular, various machine learning approaches are developed to help explain at least 85% of the design variance when building a model to predict potential customer needs and wants. These approaches include k-means clustering, self-organizing maps, fuzzy k-means clustering, and decision trees, all supporting a vector machine to evaluate and extract conscious and subconscious customer needs and wants. A model capable of accurately predicting customer needs and wants for at least 85% of classified design attributes is thus obtained. Further, an analysis capable of determining the best design attributes and features for predicting customer needs and wants is also achieved. As the information analysed can be utilized to advise the selection of desired attributes, it is fed back in a closed-loop of the manufacturing value chain: design → manufacture → management/service → → → design... For this, a total of 4 case studies are undertaken to test and demonstrate the efficacy and effectiveness of the framework developed. These case studies include: 1) an evaluation model of consumer cars with multiple attributes including categorical and numerical ones; 2) specifications of automotive vehicles in terms of various characteristics including categorical and numerical instances; 3) fuel consumptions of various car models and makes, taking into account a desire for low fuel costs and low CO2 emissions; and 4) computer parts design for recommending the best design attributes when buying a computer. The results show that the decision trees, as a machine learning approach, work best in predicting customer needs and wants for smart design. With the tested framework and methodology, this thesis overall presents a holistic attempt to addressing the missing gap between manufacture and customisation, that is meeting customer needs and wants. Effective ways of achieving customization for i4 and smart manufacturing are identified. This is achieved through predicting potential customer needs and wants and applying the prediction at the product design stage for agile manufacturing to meet individual requirements at a mass production cost. Such agility is one key element in realising Industry 4.0. At the end, this thesis contributes to improving the process of analysing the data to predict potential customer needs and wants to be used as inputs to customizing product designs agilely