A normative experimental study was undertaken to establish whether engaging in positive, negative, and neutral mental imagery affected the reaction rate of participants to positive, negative, and neutral word stimuli. The sample consisted of computer literate, English speaking participants with no history of clinical disorders. A total of 80 participants took part in the study, with 40 participants from either gender. The results of a factorial ANOVA indicated that the type of mental imagery engaged in had a significant effect on the rate at which participants responded to stimuli (p=.00023, F=8.4057), whilst the emotional valence of the stimuli did not have a significant effect (p=.30503, F=1.1877). However, the interaction between the type of mental imagery and the emotional valence of the stimuli was highly significant (p=.00794, F=3.4576), thereby indicating that engaging in positive or negative mental imagery did bias participants towards a faster reaction rate to positive or negative stimuli respectively. / M. A. (Psychology) / Psychology

Submitted by Adriana Alves Rodrigues (aalves@espm.br) on 2017-11-22T15:02:28Z No. of bitstreams: 1 ANDRE SILVA DE CARVALHO.pdf: 3017440 bytes, checksum: 72f0dd79324eb16e16c0fca2fea756db (MD5) / Approved for entry into archive by Adriana Alves Rodrigues (aalves@espm.br) on 2017-11-22T15:02:51Z (GMT) No. of bitstreams: 1 ANDRE SILVA DE CARVALHO.pdf: 3017440 bytes, checksum: 72f0dd79324eb16e16c0fca2fea756db (MD5) / Approved for entry into archive by Ana Cristina Ropero (ana@espm.br) on 2017-11-23T10:56:03Z (GMT) No. of bitstreams: 1 ANDRE SILVA DE CARVALHO.pdf: 3017440 bytes, checksum: 72f0dd79324eb16e16c0fca2fea756db (MD5) / Made available in DSpace on 2017-11-23T10:56:31Z (GMT). No. of bitstreams: 1 ANDRE SILVA DE CARVALHO.pdf: 3017440 bytes, checksum: 72f0dd79324eb16e16c0fca2fea756db (MD5) Previous issue date: 2017-03-24 / Being innovative in a more and more competitive market can be anything but trivial. There is a complex variables system to be taken into account throughout an innovation process, and hardly ever will there be enough data to support a research or decision. It is always possible to turn to human inference, or cognitive bias, when enough data is not available, or when time for decision-making is scarce. Consumer Insight technique has been used for this research purpose and aimed at lowering cognitive bias, seeking to find out what are consumers' wishes and needs so that decision-making or innovation could be supported. This paper proposes to mitigate the influence of cognitive bias, by means of data analysis techniques, in search for patterns which can identify opportunities to give both decision-making and search for innovation some support. In order to achive this purpose, unstructured data from 26.514 telephone talks had in a big financial market company between 01.12.2016 e 31.12.2016 have been used. Analysis has been carried out with the transcript from voice into text concomitantly with Text Mining and Social Network analysis. The results have led us to identify main client demands from a sales perspective, cancellation resquest, as well as the reason for inefficiency in offering new products from elements of higher centrality identified in the word association networks. It is implied that the combined use of analytical techniques applied to unstructured data may give rise to findings in which cognitive bias is lower. / Em um mercado cada vez mais competitivo, ser inovador pode ser um diferencial, porém não é uma atividade trivial. Existe um sistema de variáveis complexas que deve ser considerado ao longo de um processo de inovação e nem sempre há dados suficientes que suportem uma pesquisa ou decisão. A inferência humana, ou viés cognitivo, pode ser uma alternativa quando não existem dados suficientes ou quando o tempo para a tomada de decisão é menor que o necessário. A técnica de Consumer Insight foi utilizada nesta pesquisa com o objetivo de diminuir o viés cognitivo, buscando descobrir os anseios e necessidades do consumidor, para suportar o processo de tomada de decisão ou inovação. Este estudo apresenta uma proposta para mitigar a influência do viés cognitivo, a partir de técnicas de análise de dados, em busca de padrões que possam identificar as oportunidades para suportar o processo decisório ou a busca pela inovação. Neste trabalho foram utilizados dados não estruturados de 26.514 conversas telefônicas realizadas no período de 01/12/2016 a 31/12/2016, provenientes de uma empresa do mercado financeiro. A metodologia analítica consistiu na transcrição de voz para texto e no uso associado de técnicas de Text Mining e Análise de Redes Sociais. Os resultados obtidos permitiram identificar as principais demandas dos clientes na perspectiva de vendas, pedido de cancelamento e a razão da ineficiência das ofertas de novos produtos, a partir dos elementos de maior centralidade identificados nas redes de associação de palavras. Implica-se que o uso combinado de técnicas analíticas em dados não estruturados pode permitir a obtenção de achados com menor influência do viés cognitivo.

The endowment and the framing effect are widely examined cognitive biases. The experimental economics literature, using choice data gathered through an elicitation device, commonly finds evidence of these biases. Recent work by Cason & Plott (2014) shows that the interpretation of choice data as consistent with biases related non-standard preference theory could also be consistent with confusion or misconception of the game type used to elucidate preferences. I use the Cason and Plott card auction framework to analyze offers of buyers and sellers in an experimental setting with subjects from the University of New Orleans simulating 97 sellers and 90 buyers. The two games have symmetric payoffs in order to examine cognitive biases given subjects’ misconception of the game form. Subjects of both games display misconception of game form that explains both endowment and framing effects by rational confused choice; however, buyers display a much greater dispersion of offers than sellers. I estimate card implied valuation of sellers and buyers given game form misconception and find no statistical endowment effect, but I do find valuation is more uncertain in the buyer’s game. The theory of Rational Inattention predicts this lack of offer symmetry is due to the additional cognitive steps necessary in calculating buyer offers.

This thesis gives an example of how decision analytic methods can be applied to choices in the adoption of cloud computing. The lifecycle of IT systems from planning to retirement is rapidly changing. Making a technology decision that can be justified and explained in terms of outcomes and benefits can be increasingly challenging without a systematic approach underlying the decision making process. It is proposed that better, more informed cloud adoption decisions would be taken if organisations used a structured approach to frame the problem to be solved and then applied trade-offs using an additive utility model. The trade-offs that can be made in the context of cloud adoption decisions are typically complex and rarely intuitively obvious. A structured approach is beneficial in that it enables decision makers to define and seek outcomes that deliver optimum benefits, aligned with their risk profile. The case study demonstrated that proven decision tools are helpful to decision makers faced with a complex cloud adoption decision but are likely to be more suited to the more intractable decision situations.

Egg-laying hens coming from commercial hatchery go through hatchery procedures considered as stressful and engaging prolonged stress response in adult chickens. The aim of our study was to evaluate the impact of commercial hatching procedure on the affective state of chicks, on their short- and long-term memory and on their need for social reinstatement. To assess the affective state of the chicks we used a cognitive bias protocol integrating the ecological response of a chick to the picture of another chick, to an owl and to an ambiguous cue mixing features of both the chickand the owl pictures. Short-term memory was evaluated by using a delayed matching-to-sample experiment (with 10, 30,60 and 120 s delays), with conspecifics as sample stimuli. We assessed long-term memory with an arena containing multiple doors leading to conspecifics, in which a chick had to remember which door was open after a delay of one hour or three hours. Finally, we observed the need for social reinstatement through a sociality test arena allowing a chick to be more or less close to conspecifics. We found that chicks coming from commercial hatchery were in a depressive affective state compare to control group. Those chicks also showed higher need for social reinstatement and loss weight. No differences were found regarding short- and long-time working memory between the two groups, but the methods used during these experiments will be discussed. Studying how commercial procedures impact the cognition and more specifically the emotions and state of mind of chickens, is a necessary step forward into the understanding of farm animals’ welfare.

Indiana University-Purdue University Indianapolis (IUPUI) / Human-looking computer interfaces, including humanoid robots and animated humans, may elicit in their users eerie feelings. This effect, often called the uncanny valley, emphasizes our heightened ability to distinguish between the human and merely humanlike using both perceptual and cognitive approaches. Although reactions to uncanny characters are captured more accurately with emotional descriptors (e.g., eerie and creepy) than with cognitive descriptors (e.g., strange), and although previous studies suggest the psychological processes underlying the uncanny valley are more perceptual and emotional than cognitive, the deep roots of the concept of humanness imply the application of category boundaries and cognitive dissonance in distinguishing among robots, androids, and humans. First, laddering interviews (N = 30) revealed firm boundaries among participants’ concepts of animated, robotic, and human. Participants associated human traits like soul, imperfect, or intended exclusively with humans, and they simultaneously devalued the autonomous accomplishments of robots (e.g., simple task, limited ability, or controlled). Jerky movement and humanlike appearance were associated with robots, even though the presented robotic stimuli were humanlike. The facial expressions perceived in robots as improper were perceived in animated characters as mismatched. Second, association model testing indicated that the independent evaluation based on the developed indices is a viable quantitative technique for the laddering interview. Third, from the interviews several candidate items for the eeriness index were validated in a large representative survey (N = 1,311). The improved eeriness index is nearly orthogonal to perceived humanness (r = .04). The improved indices facilitate plotting relations among rated characters of varying human likeness, enhancing perspectives on humanlike robot design and animation creation.

This study examines the claim that individuals misinterpret the mean of a dataset (displayed as a scatterplot) more when the convex hull of the dataset is less representative of the data. In addition, this study also tests whether outliers in the data can predict the magnitude of error that individuals make in interpreting the mean of the dataset. Lastly, the study investigates whether individuals’ interpretations are predicted better by the mean of the convex hull than by the full dataset’s mean. The method used to conduct these investigations is through a survey, followed by several linear regression analyses. Applications of this study include improving the communication of data in economic policy and business contexts, along with broader applications in extending models that heavily rely on agents’ interpretations of information: especially bounded rationality and social norm-based models. The results show that convex hull unrepresentativeness correlates positively with error in mean interpretation; however, that the convex hull mean is not predictive of the interpretations’ direction. Overall, the study contributes to the field of visual information interpretation by investigating the effect of data structure on its interpretation – an unexplored area of research. This is done while initiating the concretization of bounded rationality in economics, by exploring the idea that individuals perceive a general shape of the information presented to them rather than a detailed, full picture. This can lead to misinterpretations whenever the general shape (convex hull) is not representative of the dataset.

Background: Digital loyalty programs collect extensive personal data, but literature has so far neglected the aspect of privacy concerns within the programs. The privacy paradox denotes the contradictory behavior amongst consumers stating privacy risk beliefs and actual behavior. Existing literature is calling for a dual perspective of the privacy paradox and digital loyalty programs to find the underlying reasons for the contradictory behavior. Purpose: The purpose of this study was to explore (1) if and when privacy concerns existed in digital loyalty programs and (2) why consumers overruled their privacy concerns in digital loyalty programs. Method: A qualitative method with 18 semi-structured interviews were conducted through a non-probability purposive sampling of consumers within digital loyalty programs. The findings were then analyzed through a thematic analysis to finally construct a model based upon the given research purpose.  Conclusion: The findings suggest that consumers experience privacy concerns in digital loyalty programs from external exposure to privacy breaches and when consumers felt their mental construct of terms and conditions were violated. Four themes were found to influence why consumers overrule their privacy concerns and share personal data with digital loyalty programs, relating to cognitive biases, value of rewards received, and digital trust for the program provider. The findings were synthesized into a model illustrating the consumer assessment of personal data sharing in digital loyalty programs and the interconnection between the influences.

Smart technology, such as the internet of things, artificial intelligence, and big data, provides consumers with a new level of convenience through various smart-connected products (SCPs). Although many experts have increasingly warned about the privacy vulnerability issues of various SCPs, consumers often underestimate privacy risks when adopting smart technology. Accordingly, this dissertation presents a literature review and three empirical studies that examine the privacy problems and suggest new concepts and models for a deeper understanding of the privacy suspension phenomenon. The first chapter reviews the literature related to the privacy suspension phenomenon by integrating the antecedents of consumers' privacy concerns. New concepts of privacy concerns, such as active and inactive privacy concerns, are suggested along with multiple propositions for the proposed privacy suspension theory, which extends the dimension of ambivalence toward trust and distrust regarding smart technology. The second chapter presents the proposed privacy–common good trade-off model and three assumptions related to privacy trade- offs, privacy reduction, and anchoring effects in the sustainable smart-connected car context. This study also discusses the relationships between governments, companies, and consumers regarding the effects of the common good of sustainability and government subsidies. The third chapter evaluates the mediation effects between sustainability, trust, privacy concerns, disclosure intentions, and purchase intentions when purchasing sustainable smart-connected cars based on the proposed sustainability–trust–behavior model. Finally, the fourth chapter provides a practical solution to resolve privacy suspension issues using the design science research approach. This study proposes privacy information type characteristics to evaluate SCPs' tailored data collection capabilities, visualizing them through a spider diagram design method with nudges. / Doctor of Philosophy / This dissertation discusses the consumer privacy suspension phenomenon when adopting smart technology. The first chapter summarizes existing studies regarding privacy concerns, trust, distrust, and ambivalence in adopting technology. It also proposes new concepts of privacy concerns and outlines the unique relationship between consumer privacy concerns and ambivalence toward trust and distrust in smart-connected products, thus helping readers understand why consumers reduce privacy concerns when adopting smart technology. The second chapter presents an empirical study that examines how consumers trade their privacy for the common good of sustainability based on the proposed privacy–common good trade-off model and outlines three key assumptions in the sustainable smart-connected car context. The third chapter discusses the roles of sustainability and trust when consumers decide to disclose their personal information and purchase sustainable smart-connected cars based on the proposed sustainability–trust–behavior model. Last, the fourth chapter provides a practical solution to improve the current inefficient privacy notification systems that cannot apply to different smart-connected products due to various smart sensors collecting different types of personal information. Thus, this dissertation contributes to a deeper understanding of the consumer privacy suspension phenomenon and how sustainability benefits can mitigate the conflicting interests between governments, companies, and consumers when adopting smart technology. In addition, the suggested practical solution using the design science research approach can help consumers make better privacy decisions when purchasing smart-connected products.

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