The advent of the industrial revolution has brought a great number of changes in the functioning of various processes in manufacturing industries. The ways and means of working have evolved exponentially with the implementation of advanced technology. Moreover, with the increasing technology, the customer demands have also been varying dynamically due to changes in customer requirements focusing on individual customization. To cope with the dynamic demand, manufacturing industries had to make sure their products are manufactured with higher quality and shorter lead times. Implementation and efficient usage of technology has provided industries with the necessary tools to achieve market demand and stay competitive by growing continuously. The transformation aims to reach the level of zero-defect manufacturing and ensure higher first-time right yield capability with minimum utilization of available resources. However, technological advancements have not developed the quality inspection process of the manufacturing industry at the same level as other processes. Due to this, the quality inspection processes are still human dependent which requires a highly skilled human operator to perform inspection procedures using sensory abilities to detect deviations. Research suggests that human quality inspection is prone to errors due to fatigue as the process is continuous, strenuous, and tedious work. The efficiency of human inspection is around 80% which becomes a chronic problem in safety-critical and high-value manufacturing environments. Moreover, with the increasing level of customization and technology, the products are becoming more complex with intricate shapes and only human inspection is not enough to meet the customer requirements. Especially in the case of automotive industry in Body in White applications, human inspection of outer body panels, engine parts with tighter tolerances alone does not make the cut. Advancements in the field of metrology have led to the introduction of Coordinate measuring machines (CMM), which are classified as contact and non-contact measuring machines. The measurements are performed offline away from the production line, using the sampling method. The contact measuring machines are equipped with touch trigger probe devices that travel all over the part to make a virtual image of the product which is time-consuming but accurate. Whereas the noncontact measuring machines are equipped with laser scanners or optical devices which scan the part and develop a virtual model which is fast but has accuracy and repeatability issues due to external factors. But coordinate measuring machines have proven to be bottlenecks as they were not able to synchronize with the production pace and could not perform aninspection on all the produced parts, which would help in collecting data. The gathered data can be used to analyse root causes and generate trends in defect detection. With the advancements in non-contact measuring systems, automotive industries have also realized the potential of implementing inline measurement techniques to perform quality inspection. The non-contact measuring system consists of a robotic arm or setup which is equipped with a camera, sensors, and a complex algorithm to identify defects. This provides the robotic arm with machine vision which is works by taking a series of images of the product from various and process these images to detect deviations using digital image processing techniques. The inline measurement has proven to be accurate, fast, and repeatable to be implemented in synchronization with the production line. Further, the automotive industries are moving towards hybrid inspection systems which capitalize on the measuring speed of the robot and the fast decision-making ability of human senses.

Résumé indisponible. / The VIPAFLEET project aims at developing a framework to manage a fleet of IndividualPublic Autonomous Vehicles (VIPA). We consider a fleet of cars distributed at specifiedstations in an industrial area to supply internal transportation, where the cars can beused in different modes of circulation (tram mode, elevator mode, taxi mode). The goalis to develop and implement suitable algorithms for each mode in order to satisfy all therequests either under an economic point aspect or under a quality of service aspect, thisby varying the studied objective functions.We model the underlying online transportation system as a discrete event basedsystem and propose a corresponding fleet management framework, to handle modes,demands and commands. We consider three modes of circulation, tram, elevator andtaxi mode. We propose for each mode appropriate online algorithms and evaluate theirperformance, both in terms of competitive analysis and practical behavior by computationalresults. We treat in this work, the pickup and delivery problem related to theTram mode and the Elevator mode the pickup and delivery problem with time windowsrelated to the taxi mode by means of flows in time-expanded networks.

Abstract not available.

With the gradual upgrade of fresh food consumption in China, the integration of online platforms and retail entities has brought more convenient and diverse fresh food consumption experiences to customers. This thesis is to explore how the customers loyalty in Chinese fresh e-commerce are affected by online and offline customer experience. This paper draws on strategic experience modules and situation experience theory and proposes three influencing factors respectively according to the two situations of online and offline. Specifically, this thesis analyzes the impact of the aesthetic experience, online service experience, and virtual community sense experience, environmental experience, service staff experience and community sense experience on customer loyalty. As a leader of fresh e-commerce, Hema Fresh has achieved great success especially during this epidemic and has been recognized by Chinese customers. This study collects 298 online questionnaires from Hema Fresh’s customers in China and uses SPSS for regression analysis to test these six factors. Empirical results show that enhancing customer aesthetic experience, online service experience, environmental experience and community sense experience can improve customer loyalty of fresh e-commerce in China, but our results do not show that virtual community sense experience and service staff experience can enhance customer loyalty. Meanwhile, this study finds that the effects of online and offline situations on customer loyalty of fresh e-commerce are different. By providing the experience and background of Chinese fresh e-commerce, it enriches the research on fresh e-commerce. Also, this study explores different types of customer experience impact on customer loyalty from the online and offline situations of customer consumption, contributing to the research on customer experience and provides implications for Chinese fresh e- commerce to improve customer loyalty.

In modern times, live video streaming events in companies has become an increasingly relevantmethod for communications. As a platform provider for these events, being able to deliverrelevant recommendations for event scheduling times to users is an important feature. A systemproviding relevant recommendations to users can be described as a recommender system.Recommender systems usually face issues such as having to be trained purely offline, astraining the system online can be costly or time-consuming, requiring manual user feedback.While many solutions and advancements have been made in recommender systems over theyears, such as contributions in the Netflix Prize, it still continues to be an active research topic.This work aims at designing a recommender system which observes users' past sequentialscheduling behavior to provide relevant recommendations for scheduling upcoming live videoevents. The developed recommender system uses reinforcement learning as a model, withcomponents such as a generative model to help it learn from offline data.

Under det senaste decenniet har e-handeln expanderat och det gångna årets pandemi i form av covid-19 har bara ökat denna tillväxt. Stora delar av beklädnadshandeln har i samband med detta övergått från att ske offline till online. Syftet med denna studie är att undersöka vad som får konsumenten att välja att handla i fysisk butik vs e-handel. För att uppnå syftet använder sig studien av två kvalitativa metoder i form av fyra fokusgruppsdiskussioner med erfarna konsumenter online och offline inom generation Y. Vidare genomförs det sex semistrukturerade intervjuer med respondenter från tre företag som driver både fysisk butik samt e-handel. Insamlad data analyserades utifrån en tematisk analys. Resultatet visar att konsumenterna utnyttjar fysiska butiker genom dess tillgång till provrum och personlig service samt att e-handel uppmanar mer till köp genom marknadsföring online. Genom analys av resultatet dras slutsatsen att tillgänglighet, utbud och pris är de främsta drivkrafterna till vilken kanal som används av konsumenterna. Att närvaro på sociala medier och recensioner i digitala kanaler påverkar konsumenterna är också slutsatser som dras.

Background: The retail sector is rapidly developing over the past years. Retailers are investing more efforts and resources to provide a seamless experience through multiple channels. These developments led to significant changes in customer behaviour. Customers buying activities and way of selecting the products and retailers faced different changes and developments. The online retailing sector is entitled to continuous development. The latest development was due to the Covid-19 global pandemic that came without any previous notice. The customer behaviour starts adopting the digital online channels in most of their needs and wants. The appearance of new customer behaviour patterns due to Covid-19 lead to the emergence of new customer behaviour.Purpose: This study is of an exploratory and constructive nature. It is concerned with deepening the knowledge about the change in customer buying behaviour brought by Covid-19 on the retailing sector. The aim of the study is to identify and test new behavioural patterns that would influence the Swedish millennials’ in selecting between online and offline stores for shopping and buying fashion products.Method: An abductive approach was followed in this paper. Mixed methods of both qualitative and quantitative were used to fulfil the purpose of this exploratory research. The research followed a sequential exploratory design of two data collection phases. Theiiempirical data was conducted from (4) focus groups sessions with a total number of (20) interviewee, and (94) relevant responses from a web-based survey.Conclusion: The study has revealed two significant findings and contributed to propose a conceptual model. The fruitful results of this study are: (1) there is a vast customers’ migration towards online stores. (2) there are new behavioural patterns related to Covid-19 that are influencing the customer buying behaviour. (3) A proposed conceptual model which is concerned with the factors influencing the customer buying behaviour in selecting between online and offline fashion stores.

The aim of this thesis is to explore how Telegram is used as a tool for social media protests inRussia. The thesis will focus on the relationship between offline and online protests andmainly discuss the application Telegram in this context. It will analyze the positive andnegative attributes, as well as the effects and future of Telegram as a tool for social mediaprotests. It will do this by drawing on theory on political socialization, as well asmediatization, while also looking at various research that has been made on the subject. Theresult shows that Telegram is used as a tool for the Russian people to express their longingand wish for freedom, while it also shows that the Russian state is trying to prevent harm tothe Russian people, while still harming them differently, by censoring and blocking theirsocial media. The conclusion discusses these results and questions whether Telegram canuphold the image as a platform for freedom of speech for the Russian citizens.

While online shopping has high social acceptance and support from mature related industries in China, a considerable number of consumers choose to shop offline. The purpose of this study is to explore the specific factors that give consumers the intentions to shop offline. The Theory of Planned Behavior (TPB) is adopted as the theoretical framework to give a holistic view of intention-forming. Multiple-case studies are performed in this qualitative research. We study the contents of the interviews via TPB. Fifteen Chinese consumers take part in the research as the respondents in semi-structured interviews. After coding transcriptions, we explore detailed factors and divide them into three aggregates from TPB: attitude, subjective norm and perceived behavioral control. The analysis of the interviews also supports the transformation of three dimensions of TPB.

Background: Customers find great psychological satisfaction and pleasure when shopping. Customer satisfaction is crucial for a business's success, and increasing it will strengthenfinancial performance and competitiveness. Offline shopping still dominates the customersindustry, although customers are increasingly choosing online shopping as a result offast-growing technological developments in society. However, physical experiences shouldnot be left behind due to customer’s satisfaction from the instant gratification they desire. Purpose: The purpose of this paper is to explain how customer perceived value, customerexpectations, and touch experience have an impact on customer satisfaction in an offlineshopping context. Methodology: This research is conducted through a deductive and quantitative approach,which has an explanatory aim. Three hypotheses have been deducted from theoreticalconcepts found from previous research. The data collection method was collected through aninternet-based, self-completion questionnaire, to see if the hypotheses were supported or not.A total of 105 respondents participated in the study. Findings: The findings indicate that customer perceived value H1, which explains a positiveimpact on customer satisfaction in the context of offline shopping, cannot be supported due tostatistical insignificance. Customer expectation, as presented through H2, and touchexperience, as presented through H3, were found to have a statistically significant andpositive impact on customer satisfaction. The conceptual model was revised in this studybased on the new findings, retaining the acceptable assumptions as the new model. Conclusion: In offline shopping, the positive impact of customer expectation on customersatisfaction is the most obvious, followed by the touch experience. Customer perceived valuehas no positive impact on customer satisfaction, and the reason for this situation may be thatthe perceived value of customers differs among different consumption levels.