The consumer electronics (CE) industry has high turnovers and a growing demand, such as on the home entertainment segment. At the same time, it generates e-waste of the order of a dozen million tons, about one quarter of the world's total. With the purpose of improving the environmental performance of businesses, the Waste Electrical and Electronic Equipment (WEEE) Directive was put in place in Europe. Given the high competitive environment of this industry, WEEE could be a clue for competitive edge. To create an environmental and economic win-win situation, however, companies have to master reverse logistics (RL). This is particularly challenging in fast clockspeed environments, as it is the case for the CE industry. In this paper, we develop a theoretically and empirically grounded diagnostic tool for assessing a CE company's RL practices and identifying potential for RL improvement, from a business perspective. To theoretically ground the tool, we combine specific CE literature with general theory on reverse logistics management and performance improvement. To empirically ground the tool, we collect field data by combining quantitative (a multiactor survey) with qualitative (interviews and company visits) methods. We demonstrate how our tool can be used to create awareness at senior management about the reverse logistics maturity state.
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Previous investigations of consumer subcultures in the CCT tradition focused primarily on consumer behaviours, feelings, experiences and meanings of consumption. This paper advocates that in order to deeply understand and interpret a particular subculture, researchers in consumer culture should consider more thoroughly the interaction between consumers and producers in consumption markets. This argument is illustrated with a research project on lifestyle sports. From the results of this study it appears that producers play a vital and interdependent role in meaning and interpretation processes. It is argued that processes in which consumers give meaning to activities can not be isolated from the processes in which producers ascribe meanings to activities, settings and markets. In this 'circuit of culture', production and consumption are not completely separate spheres of existence but rather are mutually constitutive of one another (Du Gay, Hall, Janes, Mackay, & Negus, 1997).
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Individual and unorganized sports with a health-related focus, such as recreational running, have grown extensively in the last decade. Consistent with this development, there has been an exponential increase in the availability and use of electronic monitoring devices such as smartphone applications (apps) and sports watches. These electronic devices could provide support and monitoring for unorganized runners, who have no access to professional trainers and coaches. The purpose of this paper is to gain insight into the characteristics of event runners who use running-related apps and sports watches. This knowledge is useful from research, design, and marketing perspectives to adequately address unorganized runners’ needs, and to support them in healthy and sustainable running through personalized technology. Data used in this study are drawn from the standardized online Eindhoven Running Survey 2014 (ERS14). In total, 2,172 participants in the Half Marathon Eindhoven 2014 completed the questionnaire (a response rate of 40.0%). Binary logistic regressions were used to analyze the impact of socio-demographic variables, running-related variables, and psychographic characteristics on the use of running-related apps and sports watches. Next, consumer profiles were identified. The results indicate that the use of monitoring devices is affected by socio-demographics as well as sports-related and psychographic variables, and this relationship depends on the type of monitoring device. Therefore, distinctive consumer profiles have been developed to provide a tool for designers and manufacturers of electronic running-related devices to better target (unorganized) runners’ needs through personalized and differentiated approaches. Apps are more likely to be used by younger, less experienced and involved runners. Hence, apps have the potential to target this group of novice, less trained, and unorganized runners. In contrast, sports watches are more likely to be used by a different group of runners, older and more experienced runners with higher involvement. Although apps and sports watches may potentially promote and stimulate sports participation, these electronic devices do require a more differentiated approach to target specific needs of runners. Considerable efforts in terms of personalization and tailoring have to be made to develop the full potential of these electronic devices as drivers for healthy and sustainable sports participation.
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Existing studies offer very limited insight into how sellers may reduce consumers' perceived risk in order to make consumer-to-consumer electronic marketplaces more successful. Contrary to these studies, the empirical investigation reported in this article acknowledges the role of sellers in enabling these computer-mediated transaction platforms. The study focuses on how information provided by sellersabout themselves (i.e., seller information) and about their products (i.e., product information) can function as risk reduction signals and how these affect a buyer's inclination to purchase. Combining signaling theory with perceived risk theory, the authors present a research model that they test using structural equation modeling with data collected in two different electronic marketplaces, includingeBay.nl. The results indicate that while product and seller information are indeed important risk reduction signals, and as such can play an important role in stimulating purchasing, the risk reduction potential of these forms of information differs across the studied risk types. This article discusses these findings and explains how they contribute to signaling theory and perceived risk theory. Based on the findings, several practical implications for sellers active in electronic marketplaces and for the intermediaries operating these transaction systems are described.
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The pervasiveness of wearable technology has opened the market for products that analyse running biomechanics and provide feedback to the user. To improve running technique feedback should target specific running biomechanical key points and promote an external focus. Aim for this study was to define and empirically test tailored feedback requirements for optimal motor learning in four consumer available running wearables. First, based on desk research and observations of coaches, a screening protocol was developed. Second, four wearables were tested according to the protocol. Third, results were reviewed, and four experts identified future requirements. Testing and reviewing the selected wearables with the protocol revealed that only two less relevant running biomechanical key points were measured. Provided feedback promotes an external focus of the user. Tailoring was absent in all wearables. These findings indicate that consumer available running wearables have a potential for optimal motor learning but need improvements as well.
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Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring.
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Instead of using a passive AC power grid for low power applications, this paper describes a smart plug for DC networks that is capable of providing the correct power to a device (up to 100W) and that allows for communication between different plugs and monitoring of energy consumption across the DC network using the Ethernet protocol in conjunction with a signal modulator to adapt the signals to the DC network. The ability to monitor consumption on a device-per-device basis allows for closer monitoring of in-house energy use and provides an easily scalable platform to monitor consumption at a macro level. In order to make this paper attractive for the consumer market and easily integrable with existing consumer devices, a generally compatible solution is needed. To meet these demands and to take advantage of the trend of charging consumer devices through USB, we opted for the recently adapted USB Power Delivery standard. This standard allows devices to communicate with the plug and demand a specific voltage and current needed for the device to operate. The purpose of this paper is to give the reader insight in the development of a proof of concept of the smart DC/DC power plug. 10.1109/DUE.2014.6827761
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This paper describes a study into consumers' reasons for buying socially responsible (SR) products, such as Fair Trade products and organic meat. As opposed to other studies, we use a qualitative approach based on 25 in-depth interviews and include several different products in the research. This leads to several new results, such as: (1) buying SR products is perceived as an imperfect moral duty; (2) low quality of SR products is a dissatisfier, but high quality not a satisfier; (3) the attitude towards SR products is related to the reputation of charitable funds; (4) the demand for SR products is negatively related to the frequency of purchasing SR products; (5) reflection on SR products raises the demand for SR products; (6) consumers that have witnessed the social problems that SR products aim to alleviate purchase more SR products. Finally, we find that the demand for different SR products is correlated: if a consumer buys one SR product, it is more likely that (s)he purchases other SR products as well.
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