This study aims to explore the perceived benefits of three-way observation on the focal areas of objectives of the activities, error-correction techniques, and group-work in an upper-intermediate class in Bilkent University School of English Language. The data was collected through five classroom observations, six post-observation reflection sheets, five focus-group interviews with the students, and five post-observation interviews with the observer. A total of 15 upper-intermediate level students, one teacher, and one observer v were involved in the study. The data was analyzed qualitatively and with the use of descriptive statistics. The findings reveal that the perceptions of the students, teacher, and observer on the focal areas show variability in terms of quantity and quality. It was also discovered that student feedback reveals more detailed information about each focal area and that each perception has its own value and should be taken into consideration by the teacher, observer and students. In this study, the researcher formed a two-step three-way observation model. According to this model, the teacher transfers the information gathered from student interviews to the observer. Based on this information, the observer presents suggestions to the teacher by creating solutions to an existing problem, developing ideas related to classroom activities or increasing the effectiveness of teaching and learning processes in a class.

This research looks into the emerging trend of circular economy which is fairly young, but have still gotten a lot of recognition in the past few years. The purpose of the research was to identify bridging activities between circular business models and customer perceived value. This gap creates a great opportunity to find correlations between these areas to hopefully construct the missing bridge to connect the phenomena. A case study was applied on an organisation having a circular business model, where its customer network was used to collect data. Two types of data collection methods were used: (1)Quantitative data collection from potential customers using a questionnaire;and (2) Qualitative data collection from existing customers with semistructured interviews. The collected data was later analysed by connecting it to existing theory of customer perceived value. The data was categorised, ranked and later inserted in a contemporary matrix created by the authors, called the Business Model Matrix. The whole research was lastly presented as a conceptual model with the intent to generalize the methodology so it could be applied on other organisations. The model consists of five steps: (1) Research, (2) Data collection, (3) Translation, (4) Business Model Matrix and (5) Adaption.The authors conclude this research with: (1) It is difficult to quantify and make sense of value; (2) Standardised measurements for value has to be defined; and (3) Even though it might be difficult to interpret the business model matrix result, it might give a good overview of what the customers likes which can increase competitiveness in the long-term. Suggested future research lies in standardising value and looking into perceived value from other actors rather than customers as well.

Purpose The purpose of the study is to explain the perceived benefits and perceived privacy concerns of AI’s effects on willingness to disclose personal information to AI while explaining the moderating effect of perceived knowledge of AI.  Design/methodology/approach With the explanatory purpose in mind was firstly a deductive approach of research applied. The researchers further applied a quantitative approach of research in the form of a questionnaire. A total number of 193 responses of the questionnaire was validly collected. Furthermore, 10 hypotheses were conducted in order to investigate the relationships within research. Findings The findings are that perceived knowledge of AI does not have a positive moderating effect on any of the perceived benefits of AI nor perceived concerns of AI effectiveness on willingness to disclose personal information to AI. The findings also show that perceived privacy concerns of AI have a negative effect on willingness to disclose personal information to AI. Perceived personalization benefits, perceived health benefits and perceived financial benefits of AI have a positive effect on willingness to disclose personal information to AI.  Research contributions/limitations The research contributes to current research by highlighting the importance of context in regard to privacy calculus in order to improve on the model’s ability to explain variations. The research is limited by its data being skewed towards younger people and thus the study is representative of a younger Swedish sample.  Practical implications The research shows that it is important for both businesses and policy makers to take into consideration that individuals possess a higher perceived privacy concern of AI in comparison to the benefits when it comes to disclosing personal information to AI. Highlighting the importance of educating individuals in how AI actually function, as it is implied that the benefits are valued but it does not make individuals more willing to disclose personal information to AI.   Originality/value The originality of the study is that it makes use of the context of AI in relation to the privacy calculus, which has not been done before. Additionally, incorporating specific benefits as opposed to explaining the general perception of AI benefits, the study is able to explain more specifically how different benefits of AI affect individual’s willingness to disclose personal information to AI.

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Cotton makes up a majority of the world’s fiber market, with genetically engineered (GE) cotton the current staple of the US agricultural landscape. With GE cotton’s overall acceptance for US farmers and manufacturers, it is of concern that the majority of literature concerning GE crops primarily compares negative attitudes towards GE food crops in stricter economies such as the European Union. Due to the inadequate literature regarding both the market advantages and consumer perceptions of GE cotton specifically, this study was conceived to provide marketers with a baseline analysis of the factors that affect US consumers’ current attitudes (knowledge, risk perceptions, etc.) regarding GE cotton. Multiple regression analyses were used for our models which measured purchase intentions towards GE cotton and perceived risks of GE cotton based on both intrinsic and extrinsic factors. Paired and single t-tests were performed to predict the current positioning of GE cotton as a marketable alternative to organic and conventional cotton, and to determine which institutions consumer’s trust most for information on the risks and benefits of GE cotton. Our studies showed that while knowledge of cotton and agriculture is low, GE cotton was regarded more positively than conventional cotton with the potential to improve in consumer’s opinions. According to our findings, by efficiently communicating the benefits of GE cotton through trusted channels of communication (i.e. scientists, consumer organizations, the media), particularly addressing ethical concerns, policy regulation, and how the product is useful to the consumer individually, GE cotton could become a comparative market alternative to organic, at a greater available supply. / text

The purpose of the study was to explore the psychosocial factors involved in the susceptibility, experience and rehabilitation of injuries sustained in long-distance running in order to develop a biopsychosocial theoretical model that will help explain the experience of injury and the successful rehabilitation thereof in long-distance running. The study was approached from a biopsychosocial theoretical perspective. A mixed methods research design with the purpose of expansion and using 15 case studies was employed. Purposive sampling with a snowballing effect was used to select the 15 long-distance runners who were injured or had recently recovered from injury. Semi-structured interviews were conducted with each of the participants. Furthermore, each participant completed the Myers-Briggs Type Indicator. An examination of the participants’ experiences of injury reveals that injury has an effect on and is affected by the following factors: running history and training program; perceived benefits and disadvantages of running; personal understanding of injury; personality factors; psychological responses to injury; perceived causes of injury; approach to rehabilitation; and coping mechanisms. Furthermore, there is an inherent interplay of biological or physical, psychological and social processes involved in the experience of injuries sustained in long-distance running. Based on the findings of the study, the biopsychosocial model of long-distance running injuries is proposed. Although the model emanates from the experiences of the 15 participants in the study, it may be applied to long-distance runners in general. A long-distance runner’s experience of running is the core of the model. The model depicts how each of the factors noted previously has an effect on and is affected by injury; thus, showing the integral relationship between injury and each of the factors. Furthermore, the biopsychosocial nature of the model is also portrayed in the model. Cognizance is also taken that all long-distance runners are individuals and may respond to injury in a unique manner. / Thesis (PhD)--University of Pretoria, 2012. / Psychology / unrestricted

The Internet of Things (IoT) has been acknowledged as one of the most innovative forms of technology since the computer, because of the influence it can have on multiple sectors of physical and virtual environments. The growth of IoT is expected to continue, by 2020 the number of connected devices is estimated to reach 50 billion. Recent developments in IoT provide an unprecedented opportunity for personalised services and other benefits. To exploit these potential benefits as best as possible, individuals are willing to provide their personal information despite potential privacy breaches. Therefore, this paper examines factors that influence the willingness to disclose personal information in the use of IoT in South Africa (SA) with the use of the privacy calculus as the theoretical underpinnings of this research. The privacy calculus accentuates that a risk-benefit trade off occurs when an individual decides to disclose their personal information, however, it is assumed that there are more factors than perceived risks and perceived benefits that influence information disclosure. After analysing previous literature, this study identified the following factors; information sensitivity, privacy concerns, social influence, perceived benefits, (perceived) privacy risks and privacy knowledge as possible key tenants in relation to willingness to disclose personal information. This research took on an objective ontological view, with the underlying epistemological stance being positivistic. The research incorporated a deductive approach, employing the use of a conceptual model which was constructed from a combination of studies orientated around privacy, the privacy calculus and the privacy paradox. Data for this research was collected using the quantitative research approach, through the use of an anonymous online questionnaire, where the targeted population was narrowed down to the general public residing within SA that make use of IoT devices and/or services. Data was collected using Qualtrics and analysed using SmartPLS 3. SmartPLS 3 was used to test for correlations between the factors which influence information disclosure in the use of IoT by utilising the complete bootstrapping method. A key finding was that the privacy paradox is apparent within SA, where individuals pursue enjoyment and predominantly use IoT for leisure purposes, while individuals are more likely to adopt self-withdrawal tendencies when faced with heightened privacy concerns or potential risks.

Small apparel retailers face extreme competition with larger retailers. Large retailers have the upper hand in resources to stay updated with various trends, specifically social media. Social media has lowered the barriers to enter the retail industry. However, once these small retailers enter, half of them fail because they don't attract and retain customers. Small-medium enterprises (SMEs) greatly impact the economy, so it is important to study various facets of their business to increase performance. The purpose of this study is to investigate customer's development of social capital (i.e. affiliation, responsiveness, shared values, norm of reciprocity) in small apparel retailer's Instagram page that ultimately lead to purchase intentions for the retailer. Perceived benefits (i.e. perceived usefulness, perceived enjoyment) are also investigated in relation to purchase intentions. More specifically, social bonding, brand identification and trust are examined as mediating variables between the perceived level of social capital, perceived benefits and purchase intentions. Over a 3-month period, 200 responses were collected from students at a southern university. The findings reveal that younger customers develop a relationship with retailers on Instagram and it transfers to behavioral outcomes towards the retailer. The theoretical contribution of this study draws from the lack of literature for small apparel retailer and social capital built in Instagram, leading to purchase intentions. Managers can implement the findings into their social media marketing strategies to improve business performance. Lastly, this study has methodological limitations that creates opportunity for future studies.

Purpose: The purpose of the study is to investigate how consumers reason about personalized online advertising. Research questions:  Do consumers perceive the risks and benefits of personalized online advertisements? How do consumers adapt their behavior based on the risks and benefits perceived by online personalized advertisements?   Methodology: This study is implemented using a qualitative research method and a deductive approach. The empirical data for the study was gathered through twenty individual semi-structured interviews. The researchers employed thematic text analysis to systematically process the acquired data, which was subsequently examined using behavioral-science theories.  Analysis & Conclusion: According to the findings, consumers believe that they receive more relevant ads as a result of advertisements being tailored to them and are willing to share their personal information in order to receive personalized ads. The risks of personalized advertisements stem from privacy issues. However, there is a difference in perceived risks between consumers, in that consumers who are more aware of how their personal information is used by companies see greater risks with personalization. Consumers' attitudes towards personalized ads from companies that they have never signed up for, interacted with or shopped from differ depending on the communication channel through which the ads are displayed. This is because personalized advertisements via e-mail, as opposed to advertisements on websites, are considered to include more personal information such as customer name and e-mail address. As a result, consumers perceive that it is more worrying to receive personalized emails without having supplied their name or email address to the email senders than seeing personalized advertising on websites with which they have never engaged before.

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