Instagram has become an unsuspecting pulpit – seemingly caught off guard – for those determined to spread a militant message of Islamic State terror. Graphic, fanatical and oftentimes heavily photoshopped images weave through Instagram’s labyrinth of sunset snaps and gym selfies to advance a curious manifestation of cause-related self-promotion.
Abstract: Electronic and electrical waste (e-waste) is growing fast. The purpose of this study is to examine young consumers’ purchase intention of refurbished electronic devices (REDs) such as laptop, tablet, mobile phone and game console. From literature review the factors that influence young consumers’ purchase intention were identified as ‘environmental awareness’, ‘social acceptance’, ‘seller/brand reputation and availability’, and ‘affordability and value’. For each factor a few statements were developed and used as independent variables in a questionnaire. One statement was added about purchase intention as dependent variable. A Pearson correlation coefficient test us showed a clear positive correlation of ‘environmental awareness’ and ‘affordability and value’ with the intention to purchase REDs, but not for the other two factors. This analysis contributes to knowledge on young consumers’ perceptions of refurbished electronic devices and can inform the design of innovative value propositions and new business models for REDs that contribute to a circular economy
MULTIFILE
A previous paper published in this journal proposed a model for evaluating the location of fingermarks on two-dimensional items (de Ronde, van Aken, de Puit and de Poot (2019)). In this paper, we apply the proposed model to a dataset consisting of letters to test whether the activity of writing a letter can be distinguished from the alternative activity of reading a letter based on the location of the fingermarks on the letters. An experiment was conducted in which participants were asked to read a letter and write a letter as separate activities on A4- and A5-sized papers. The fingermarks on the letters were visualized, and the resulting images were transformed into grid representations. A binary classification model was used to classify the letters into the activities of reading and writing based on the location of the fingermarks in the grid representations. Furthermore, the limitations of the model were studied by testing the influence of the length of the letter, the right- or left-handedness of the donor and the size of the paper with an additional activity of folding the paper. The results show that the model can predict the activities of reading or writing a letter based on the fingermark locations on A4-sized letters of right-handed donors with 98 % accuracy. Additionally, the length of the written letter and the handedness of the donor did not influence the performance of the classification model. Changing the size of the letters and adding an activity of folding the paper after writing on it decreased the model’s accuracy. Expanding the training set with part of this new set had a positive influence on the model’s accuracy. The results demonstrate that the model proposed by de Ronde, van Aken, de Puit and de Poot (2019) can indeed be applied to other two-dimensional items on which the disputed activities would be expected to lead to different fingermark locations. Moreover, we show that the location of fingermarks on letters provides valuable information about the activity that is carried out.
