Yes / The purpose of this research is to establish the necessary and sufficient conditions for food safety and security during pandemic outbreaks, focusing on the case of COVID-19 to ensure resilience of the food supply chain. The study emphasises on the complexity theory of fuzzy set Qualitative Comparative Analysis (fsQCA), to establish a result-driven definition of Industry 5.0 (I5.0) during and post pandemics. The results of this study revealed that a combination of conditions derived from pandemic policy related reforms and I5.0 enablers will assist manufacturers and suppliers in establishing food safety and security during and post the COVID-19 era in a developing economy. Food safety and security being the goal, based on a survey of 140 food companies, this study provides insights to manufacturers and policymakers to enable selective implementation of I5.0 enabling technologies and pandemic policies.

Yes / Purpose – The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains. Design/methodology/approach – We used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model (PLS-SEM) was conducted to assess the research’s hypothesised relationships. Findings – We provide empirical evidence to support the contributions of I5.0 drones for cleaner production. Our findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations such as reducing plant diseases which invariably enhances cleaner production. However, there is less inclination to drones adoption if the aim was pollution reduction, predicting seasonal output and addressing workers health and safety challenges. Our findings outline the need for awareness to promote the use of drones for addressing workers hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies. Originality – This is the first study to address I5.0 drones' adoption using a sustainability model. We contribute to existing literature by extending the sustainability model to identify the contributions of drones use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.

The Fourth Industrial Revolution, known as Industry 4.0, has ushered in a new era of technological advancement and disruption across Manufacturing Industries. As organizations embrace digital technologies, artificial intelligence, and automation, the workforce faces profound changes in job roles, skill requirements, and training needs. Several challenges are faced by industries during this Industrial transformation. This research begins by focusing on Industry 4.0 and Industry 5.0, understanding there evolving concept. Through comprehensive literature review, the challenges and practices faced during this Industrial transformation and SDGs are discussed. Following the literature review, survey and interview questions were drafted trying to dug deeper into aspects that the literature could not fully capture. Furthermore, the relation between this Industrial Transformation and SDGs were established. This research contributes to a deeper understanding of the dynamic relationship between technology, the workforce, and sustainable development. This thesis report serves as a valuable resource for policymakers, business leaders, educators, and researchers seeking to navigate the transformative landscape of Industrial Transformation and its implications for a rapidly evolving workforce and sustainabledevelopment. / Den fjärde industriella revolutionen, känd som industry 4.0, har introducerat en ny era av teknologisk framsteg och förändringar inom tillverkningsindustrin. När organisationer omfamnar digitala teknologier, artificiell intelligens och automation står arbetskraften inför djupgående förändringar i arbetsroller, kompetenskrav och utbildningsbehov. Under denna industriella omvandling möter företag flera utmaningar. Denna forskning börjar med att fokusera på industry 4.0 och industry 5.0 och förstå deras utvecklande koncept. Genom en omfattande litteraturgenomgång diskuteras de utmaningar och metoder som möter denna industriella omvandling samt deras koppling till hållbarhetsmålen (sdgs).Efter litteraturgenomgången utformades enkät- och intervjuförfrågningar för att fördjupa förståelsen för aspekter som litteraturen inte kunde fånga helt. Vidare etablerades sambandet mellan denna industriella transformation och hållbarhetsmålen. Denna forskning bidrar till en djupare förståelse av den dynamiska relationen mellan teknologi, arbetskraften och hållbar utveckling.Denna avhandling tjänar som en värdefull resurs för beslutsfattare, företagsledare, utbildare och forskare som söker navigera i det föränderliga landskapet av industriell transformation och dess konsekvenser för en snabbt utvecklande arbetskraft och hållbar utveckling.

Background:  Green Marketing faces an upward trend; global well-being becomes more and more important while at the same time the new age of Industry 5.0 is ahead. All those components contribute to increasing environmental business activities.      Purpose:   The purpose of the study is to elaborate under which considerations Green Marketing can be successfully implemented by businesses in respect of the changing environmental processes lead by Industry 5.0 and the associated movement towards environmental and global well-being.    Method:  This study is of qualitative nature and follows an inductive interpretivist approach. The literature review as secondary research data is complemented by primary data conducted through mixed methods of expert interviews and a focus group.   Conclusion:  Likewise, opportunities and challenges within environmental business appear. The developed framework illustrates the interconnection inter alia of green marketing and Industry 5.0 that contribute to a successful execution to reach global well-being. Summarizing a holistic approach towards global well-being is indispensable.

Background: The use of technologies and digitization has become unavoidable in recent years to improve organizational efficiency and competitiveness. Even though companies are still adopting Industry 4.0 technologies, the next industrial revolution is approaching. Researchers argue for the importance of human-centricity in industries to provide benefits for all stakeholders involved. However, in literature, it is unexplored how human-centricity can be achieved with Industry 4.0 technologies, especially in a supply chain context.  Purpose: The purpose of this study is to explore how Industry 4.0 technologies can support a human-centric supply chain. Method: An exploratory, qualitative study was conducted to gain an in-depth understanding of the research phenomenon. A holistic multiple case study provided empirical findings through semi-structured interviews. An inductive thematic analysis has been performed, which enabled the findings to emerge from the data. Conclusion: The human-centric focus is being acknowledged and the case companies are actively focusing on technological implementations to improve it. Thecreation of a safe, creative, and attractive work environment, where workers are actively involved in implementation processes, and heavy labor and repetitive tasks are replaced, will result in a positive cycle towards human-centricity and technological innovations. Companies will first have to overcome implementation barriers and focus on technological innovations that support human-centricity within the boundaries of the firms. This can then be followed by enhanced supply chain collaborations.

The workforce rostering for tomorrow’s industry needs to be reconsidered. The development of new types of production control mechanisms, like decentralized production control, impacts the effectivity and efficiency of workforce rostering methods, too. Simultaneously, social trends, like the growing demand of flexible working time models and labor shortages, take their influence on the rostering process. We are facing these requirements by developing a new rostering method which is appropriate for decentrally controlled production systems, the consideration of individual preferred working times independent of rigid shift systems and the simultaneous targeting of production-related performance variables. Therefore, we apply a simulation-based optimization approach which is based on a genetic algorithm.

In 2016, the Japanese Council for Science, Technology and Innovation (CSTI) proposed a project about sustainable smart societies known as Society 5.0. Society 5.0 advocates the use of advances in computer science and software engineering such as internet of things, artificial intelligence, augmented and virtual reality, as a way of resolving societal issues such as reducing the number of deaths in everyday traffic, reducing the amount of greenhouse gas emissions, and so forth. In this thesis, we report on the planning, execution, and results of a systematic mapping study aiming at understanding the role of software engineering in Society 5.0. To this end, we focus on identifying the main software engineering technologies enabling Society 5.0 as well as the main software engineering open challenges hampering its realisation. Starting from an initial set of 829 peer-reviewed publications and by means of a rigorous selection process, we selected a final set of 58 primary studies, which we analysed following a meticulous data extraction, analysis, and synthesis process. The selected primary studies described a set of 13 software engineering technologies acting as enablers of Society 5.0. The application of these technologies comes with technical challenges. In this respect, the selected primary studies identified 9 software engineering open challenges hampering the realisation of Society 5.0.

With the development towards Industry 5.0, manufacturing companies are developing towards smart production. In smart production, data is used as a resource to interconnect different elements in the production system to learn and adapt to changing production conditions. Common objectives include human-centricity, resource-efficiency, and sustainable production. To enable these desired benefits of smart production, there is a need to use digital technologies to create and manage the entire flow of data. To enable smart production, it is essential to deploy digital technologies in a way so that collected raw data is converted into useful data that can be applied by equipment or humans to generate value or reduce waste in production. This requires consideration to the data flow within the production system, i.e., the entire process of converting raw data into useful data which includes data management aspects such as the collection, analysis, and visualization of data. To enable a good data flow, there is a need to combine several digital technologies. However, many manufacturing companies are facing challenges when selecting suitable digital technologies for their specific production system. Common challenges are related to the overwhelming number of advanced digital technologies available on the market, and the complexity of production system and digital technologies. This makes it a complex task to understand what digital technologies to select and the recourses and actions needed to integrate them in the production system. Against this background, the purpose of this licentiate thesis is to examine the selection and integration of digital technologies to enable smart production within manufacturing companies. More specifically, this licentiate thesis examines the challenges and critical factors of selecting and integrating digital technologies for smart production. This was accomplished by performing a qualitative-based multiple case study involving manufacturing companies within different industries and of different sizes. The findings show that identified challenges and critical factors are related to the different phases of the data value chain: data sources and collection, data communication, data processing and storage, and data visualisation and usage. General challenges and critical factors that were related to all phases of the data value chain were also identified. Moreover, the challenges and critical factors were related to people, process, and technology aspects. This shows that there is a need for holistic perspective on the entire data value chain and different production system elements when digital technologies are selected and integrated. Furthermore, there is a need to define a structured process for the selection and integration of digital technologies, where both management and operational level are involved. / Med utvecklingen mot Industri 5.0 utvecklas tillverkningsföretag mot smart produktion. I smart produktion används data som en resurs för att koppla samman olika element i produktionssystemet i syfte att lära sig om och anpassa sig efter förändrade produktionsförhållanden. Vanliga mål för smart produktion inkluderar resurseffektivitet, och en hållbar produktion anpassad utifrån människan. För att åstadkomma dessa önskade fördelar, behöver tillverkningsföretag använda digitala teknologier för att skapa och hantera hela dataflödet. För att möjliggöra smart produktion är det viktigt att implementera digitala teknologier på ett sätt så att insamlad rådata omvandlas till användbar data som kan tillämpas av maskiner eller människor för att skapa värde eller minska slöseri i produktionen. Detta kräver hänsyn till dataflödet inom produktionssystemet, det vill säga hela processen att omvandla rådata till användbar data som inkluderar datahanteringsaspekter som exempelvis insamling, analys och visualisering av data. För att möjliggöra ett bra dataflöde krävs det att flera digitala teknologier kombineras. Många tillverkningsföretag står dock inför flera utmaningar när de ska välja lämpliga digitala teknologier för sitt specifika produktionssystem. Vanliga utmaningar är relaterade till det överväldigande antalet avancerade digitala teknologier som finns på marknaden, samt komplexiteten hos produktionssystem och digitala teknologier. Detta gör det till en komplex uppgift att förstå vilka digitala tekniker som ska väljas och vilka resurser och åtgärder som behövs för att integrera dem i produktionssystemet. Mot denna bakgrund är syftet med denna licentiatuppsats att undersöka hur tillverkningsföretag ska välja och integrera digitala teknologier för att uppnå smart produktion. Mer specifikt så undersöker denna licentiatuppsats vilka utmaningar och kritiska faktorer som finns för att välja och integrera digitala teknologier för att uppnå smart produktion. Detta uppnåddes genom en kvalitativ multipel fallstudie med tillverkningsföretag inom olika branscher och av olika storlekar. Resultaten visar att identifierade utmaningar och kritiska faktorer är relaterade till de olika faserna av datavärdekedjan: datakällor och insamling, datakommunikation, databearbetning och lagring samt datavisualisering och användning. Generella utmaningar och kritiska faktorer som var relaterade till alla faser av datavärdekedjan identifierades också. Dessutom var utmaningarna och kritiska faktorerna relaterade till människa, process och tekniska aspekter. Detta visar att det finns ett behov av helhetsperspektiv på hela datavärdekedjan och olika element i produktionssystemet när digitala teknologier väljs och integreras. Dessutom finns det ett behov av att definiera en strukturerad process för val och integration av digital teknik, där både ledning och operativ nivå är involverade.

With an increasing demand for customized products with short delivery times, high quality, and competitive prices, manufacturing firms have to be flexible, agile, effective, and productive. In Industry 4.0, the focus were on technologies as a response to the shifted business environment. Nowadays, the integration of humans with Industry 4.0 technologies has gained interest, also known as Industry 5.0. With an increasing focus on humans, Knowledge Management (KM) and Knowledge Transfer (KT) become essential for organizations to stay at the forefront and sustain competitive advantage. Consequently, this research investigates how a manufacturing company could improve its KT to operators, especially through the use of the technology Augmented Reality (AR). This study is an exploratory case study with an inductive research approach. From a scientific perspective, this research has used an interpretivist approach. The research consisted of several phases where data from interviews, internal documents, and observations were collected and compared with previous research on the subject. Through several data sources, triangulation of data was possible andthe research questions were answered. The approach of the thesis was to, firstly, analyze current KT methods within a manufacturing setting, secondly, to analyze the required knowledge, and, thirdly, to analyze the fit of AR within KT. It was found that KT through face-to-face communication was commonly used and could create a dependability on human interaction. It was also found that documents were used as a KT method and that a discrepancy in usage could occur. Moreover, it was found that the required knowledge by operators was related to operational, problem-solving, and innovative capabilities. With regard to this, it was found that AR primarily could aid explicit KT and enhance operational capabilities. It was also found that it could aid within additional areas as well, such as being a tool for problem-solving and interdivisional KT. The thesis contributes towards academics by connecting AR for operator support to the concepts of KT and KM. The thesis also contributes towards practice by giving recommendations on the usage of AR within a manufacturing context and contributes towards the discussion of aiding peers in their workplace development. / Med en ökad efterfrågan på skräddarsydda produkter med korta livscyklar, hög kvalitet, och konkurrenskraftiga priser måste produktionssystem bli mer flexibla, agila, effektiva och produktiva. Iindustri 4.0 var fokuset att med hjälp av teknologier nå ett skifte i dessa, men med ett ökat fokus på att integrera människan kom industri 5.0. Med ett ökat fokus på människan blir kunskapshantering och kunskapshantering en viktig del för organisationer att ligga i framkant och upprätthålla konkurrenskraftighet. Därav undersöker det här arbetet hur en bearbetande produktion kan förbättra dess kunskapsöverföring till maskinoperatörer, speciellt genom användandet av teknologin Augmented Reality (AR). Denna studien är en utforskande fallstudie med en induktiv ansats och från ett metodologiskt perspektiv har studien haft en interpretivistisk ansats. Forskningen bestod av flera faser där data från intervjuer, interna dokument och observationer samlades och jämfördes med tidigare forskning inom ämnet. Genom flera datakällor var triangulering av data möjligt och forskningsfrågorna kunde besvaras. Arbetet började med att analysera dagens metodik inom kunskapsöverföring för att sedan kolla på vilken kunskap som krävs av operatörer. Sedan undersöktes hur AR kan användas inom kunskapsöverföring. Resultatet och analysen visade att face-to-face var en vanligt förekommande metod som orsakar ett beroende på människorna involverade i processen. Det visade sig även att användandet av dokument var vanligt förekommande för att överföra kunskap och att en diskrepans kan förekomma. Kopplat till kunskapen hos operatörer visade det sig att operatörer behöver kunskaper som är operativa och kunskaper relaterat till problemlösning och innovation. Sedan undersöktes AR där det visades att AR bidrar mestadels inom explicit kunskapsöverföring och bidrar till operationella kunskaper. Det visade sig även att AR bidrar inom interdivisionell kunskapsöverföring och användas som ett verktyg vid problemlösning. Arbetet bidrar inom både praktiken och till litteratur. Till litteratur bidrar arbetet genom att föra samman AR som hjälpmedel för operatörer med kunskapsöverföring och kunskapshantering. Arbetet bidrar även till praktiken genom att ge rekommendationer för användandet av AR och till kunskapsöverföring till anställda för att främja en utveckling på arbetsplatsen.

This research thesis delves into the challenges pertaining to Industry 5.0 in Sweden, with a particular focus on the Quadruple Helix Collaboration (QHC) Model. The investigation aims to shed light on how the collaboration between the government, academia, society, and industry (comprising the quadruple helix model of innovation) influences the adoption and implementation of sustainability practices in Sweden. Additionally, the article scrutinizes the challenges encountered within the realm of close collaboration and puts forth recommendations for addressing these challenges. It explores potential solutions and suggests approaches for academia to effectively alleviate these obstacles, thereby fostering sustainable growth. The ultimate goal of this study is to provide valuable insights and recommendations to academics in Sweden, enabling them to fortify their collaborations and facilitate synergistic partnerships across the various helices within the QHC framework. / Denna forskningsuppsats undersöker utmaningarna relaterade till Industri 5.0 i Sverige med särskilt fokus på Quadruple Helix Collaboration (QHC) Model. Undersökningen syftar till att belysa hur samarbetet mellan regeringen, akademin, samhället och industrin (som omfattar quadruple helix-modellen för innovation) påverkar antagandet och genomförandet av hållbarhetspraxis i Sverige. Dessutom granskar uppsatsen de utmaningar som uppstår inom området för nära samarbete och presenterar rekommendationer för att hantera dessa utmaningar. Den utforskar potentiella lösningar och föreslår tillvägagångssätt för akademin att effektivt mildra dessa hinder och främja hållbar tillväxt. Målet med denna studie är att ge värdefulla insikter och rekommendationer till akademiker i Sverige, vilket möjliggör stärkande av deras samarbeten och underlättar synergistiska partnerskap över de olika helixarna inom QHC-ramverket.