As the pandemic of COVID-19 is still affecting peoples’ lives in various ways, it is not surprising that it affects consumer behaviour as well. This paper focuses on the changes in consumer behaviour, more specifically on the changes in consumer shopping channel preferences due to the pandemic. Furthermore, it was of interest whether these changes are likely to be long-term, and influence consumer shopping behaviour in the corona-free future. To answer the research question: “How did the pandemic affect consumers’ preferred shopping channels, and are those changes long-term?” a qualitative study was conducted. The study consisted of ten interviews, five of which were with consumers who spent most of the pandemic in Sweden, and five with respondents who spent most of the pandemic in Slovakia. This way, the study compares the responses and thus changes in consumer shopping behaviour and channel preferences of consumers who have experienced different levels of restrictions and recommendations as a response to the pandemic. Indeed, Slovakia’s response to the corona pandemic was much more severe and included much more, longer-lasting, restrictions affecting/restricting consumer shopping.   The study showed that despite the countries adopting very different responses to the pandemic, the consumers changed their shopping behaviour in a rather similar way. Most of the respondents stated that they started shopping less due to the pandemic and that they shopped more online. The main reasons for these developments were (1) reduced need for new clothing during the corona pandemic, (2) stores being closed, and/or (3) consumers trying to reduce their contact with others and keep their distance. However, when asked whether these changes in their behaviour are going to persist into the far future, the responses differed. A portion of respondents stated they will continue to shop online more than prior to the pandemic, while still shopping in traditional, offline, stores as well. Some other respondents, however, stated that they will return to in-store shopping as soon as possible. From these findings, it is clear that shopping for clothes via offline channels will still be important and preferred by many, despite the rise of technologies and online shopping possibilities.   The study contributes to the literature on the corona pandemic and its effects on consumer behaviour, the field of consumer behaviour in general, consumer shopping channel preferences, channel switching intentions, omnichannel literature, and the online shopping literature.

The 3G and 4G networks have drastically improved availability and quality in data transmission for bandwidth hungry services such as video streaming and location-based services. As 3G networks are very widely deployed, there exists increased capacity requirement and transport channel allocation to simultaneous users under a particular cell. Due to this reason, adequate resources are not available, which in turn degrades both service quality and user experienced quality. This research aims at understanding the characteristics of buffer filling during dedicated channel (DCH) transmission under fixed bit-rate assumptions on a per-user level taking different services into consideration. Furthermore, the resource utilisation in terms of empty buffer durations and user throughput achieved during dedicated channel transmission are also analysed for different data services existing in the mobile networks. The traces are collected from a real network and characteristics of the traffic are analysed prior to understanding its buffer filling in Radio Network Controller (RNC) during downlink data transmission. Furthermore, the buffer is modelled with some series of assumptions on channel bit-rates and simulations are performed taking single user scenario into consideration, for different services with the help of obtained traces as input to the buffer. This research is helpful in understanding the RNC buffer filling for different services, in turn yielding possible understanding on the existing transport channel switching scenario. With the help of analysing the buffer filling for different services and transport channel utilisation, we learn that most of the data services show low DCH utilisation of approximately around 20% and also found to have 80% of the total DCH session duration with empty buffer, causing sub-optimal radio resource utilization.

The federal communications commission (FCC) has predicted that, under the current regulatory environment, a spectrum shortage may be faced in the near future. This impending spectrum shortage is in part due to a rapidly increasing demand for wireless services and in part due to inefficient usage of currently licensed bands. A new paradigm pertaining to wireless spectrum allocation, known as cognitive radio (CR), has been proposed as a potential solution to this problem. This dissertation seeks to contribute to research in the field of CR through an investigation into the effect that a primary user (PU) channel occupancy model will have on the performance of a secondary user (SU) in a CR network. The model assumes that PU channel occupancy can be described as a binary process and a two state Hidden Markov Model (HMM) was thus chosen for this investigation. Traditional algorithms for training the model were compared with certain evolutionary-based training algorithms in terms of their resulting prediction accuracy and computational complexity. The performance of this model is important since it provides SUs with a basis for channel switching and future channel allocations. A CR simulation platform was developed and the results gained illustrated the effect that the model had on channel switching and the subsequently achievable performance of a SU operating within a CR network. Performance with regard to achievable SU data throughput, PU disruption rate and SU power consumption, were examined for both theoretical test data as well as data obtained from real world spectrum measurements (taken in Pretoria, South Africa). The results show that a trade-off exists between the achievable SU throughput and the average PU disruption rate. Significant SU performance improvements were observed when prediction modelling was employed and it was found that the performance and complexity of the model were influenced by the algorithm employed to train it. SU performance was also affected by the length of the quick sensing interval employed. Results obtained from measured occupancy data were comparable with those obtained from theoretical occupancy data with an average percentage similarity score of 96% for prediction accuracy (using the Viterbi training algorithm), 90% for SU throughput, 83% for SU power consumption and 71% for PU disruption rate. / Dissertation (MEng)--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted

With the rise of the Internet and the emergence of online shopping, traditional retailing has transformed substantially. Retailers have developed multichannel strategies and, in particular, have integrated their offline channels with online channels. Such an integration of offline and online channels is associated with the concept of cross-channel integration. This cumulative dissertation aims to investigate cross-channel integration holistically from a demand point of view and a supply point of view. It consists of four independent studies embedded in an overarching introduction and conclusion part. The first study provides the conceptual base by conducting a systematic literature review. It identifies, analyzes, structures, and extracts 169 publications in the research field of cross-channel integration and concludes by suggesting two dominant paths for future research. These two research directions are addressed in three subsequent empirical studies. One empirical study focuses on the consumer perspective by investigating channel switching behavior. It finds that customers have a fundamental need for certainty within and after the buying process when it comes to channel switching. The remaining two studies are related to the supply side of cross-channel integration and investigate effects of strategies, retailers can deploy when integrating channels. One study assesses the profitability of a channel addition. It establishes that adding an offline store to online channels increases profits absolutely, but reduces the profit margin in the short run. The other study related to the supply side conceptualizes cross-channel technologies along the customer’s purchase process and experimentally assesses one of these technologies. Finally, based on the insights of the four independent studies, the dissertation concludes by summarizing the contribution and by deriving overarching implications for researchers and practitioners, the latter are equipped with a checklist for cross-channel integration.

本研究以警察廣播電臺台北臺為例，探討身為交通專業電台的警察廣播電台，在面對電視與其他廣播媒體，紛紛加入路況資訊提供的競爭下，是否仍具有其優勢？以因工作需要而必需長時間使用道路的計程車駕駛人為研究對象，探討大台北地區計程車駕駛人收聽警廣節目的主要目的為何？在什麼情況下容易轉台？節目內容與傳播設備等因素，是否也會影響計程車駕駛人的轉台意願？ 研究發現，收聽警廣台北臺節目的計程車駕駛人，只有兩種類型，一種為「計劃型」收聽，另一種則採取「再評估模式」。計程車駕駛人因警廣路況報導正確而收聽，但卻也會因為資訊不夠即時而轉台；收聽時間大多集中在上、下班的尖峰時間。最欣賞的節目主持人，則以「路況報得好、報得專業」最獲青睞，甚至有六成以上的計程車駕駛人會因為喜歡某個節目主持人，而固定收聽其節目；另外，聲音悅耳、節目多元豐富與音樂好聽與否，也是吸引計程車駕駛人是否繼續收聽的重要因素。除了路況資訊的獲得外，計程車駕駛人對於生活資訊的需求，遠高於新聞氣象、綜藝音樂及公共事務。至於車上有無其他音響設備，亦將影響計程車駕駛人的轉台行為。 / The purpose of this study is to determine whether the Police Radio Station (PRS), specifically the one in Taipei, is still necessary since television and many other forms of media provide the same service of traffic broadcasting. The research subjects for this study are Taipei taxi drivers who spend long hours on the road each day. Four questions form the basis of this study: 1. What is the main reason that taxi drivers listen to PRS? 2. Under what circumstances do they switch channels? 3. Does the content of the program affect their listening choices? 4. Does the type of broadcasting equipment affect their listening choices? The results indicate that there are two kinds of taxi drivers who listen to the programs of the PRS in Taipei. The first kind follows the "planning strategy" and the other kind follows the "re-evaluation strategy." Drivers listen to the PRS for its accuracy of traffic information; however, they will switch to another channel when there is a lack of substantial information being broadcast. Their listening time usually occurs during the rush hours, when they are getting on or getting off work. Drivers primarily prefer anchors whose information is "not only great but also professional." More than 60 percent of the drivers in this study report that they will continuously listen to one program if it is hosted by the anchor whom they favor. In addition, three other factors affect the drivers' listening habits: (1) the voice of the anchor, (2) the richness of the program content, and (3) the quality of the music being played. Besides traffic information, taxi drivers also need or desire to listen to information about other aspects of daily life, than (1) news and weather, (2) entertainment, and (3) public affairs. Finally, one other factor affects the listening behavior of taxi drivers: whether or not there is more than one form of listening device inside the car.