THE APPLICABILITY OF FINITE HOMOGENEOUS MARKOV PROCESSES IN THE STUDY OF CONSUMER LOYALTY

Markov Processes are sequential events that are related to each other stochastically. Such events, also known as states, may be such that the probability of an event occurring depends only on the previous event and not on any event prior to that. This is known as the memoryless property of Markov Processes. Certain dynamic market conditions especially with respect to the Fast-Moving Consumer Goods Sector, the Telecommunications Sector may enable the use of finite and time-homogeneous Markov Processes to study the brand switching tendency of the consumer, and thus predict consumer loyalty. In this conceptual paper, we shall study how to predict brand switching tendencies using finite, time-homogeneous Markov Processes. KEYWORDS: Markov Process, Brand Switching, Time-Homogeneous, Consumer Loyalty, Transition Matrix

External (Versus Internal) Facial Features Contribute Most to Repetition Priming in Facial Recognition: ERP Evidence

Previous event-related potential (ERP) research demonstrated four successive ERP components in the repetition priming of human face recognition: P100, N170, N250r, and N400. While these components correspond, respectively, to the four stages proposed by the interactive activation and competition (IAC) model, there has been no emphasis in past research on how internal and external facial features affect repetition priming and the sensitivity of these ERP components to item interval. This study was designed to address these issues. We used faces of celebrities as targets, including completely familiar faces, familiar internal feature faces, and familiar external feature faces. We displayed a target face either immediately following its prime (immediate repetition) or after a delay with interference from a presentation of two other faces (delayed repetition). ERP differences at P100 and N170 were nearly statistically non-significant; familiar faces and familiar external feature faces were associated with reliable ERP signals of N250r and N400 in the immediate repetition condition. For delayed repetition, however, N250r and N400 signals were only preserved for the familiar external feature faces. The differences of these ERP components suggest that, compared with internal facial features, external features of a previously presented face contribute more to brain-based facial repetition priming, particularly during the last two stages of the IAC model.

Modelado numérico de las oscilaciones frontales y ocurrencia de formación de diques de hielo del Glaciar Perito Moreno, Campo de Hielo Patagónico Sur

The present study conducts the design and development of a computational numerical model to describe the behavior of the seasonal oscillatory cycle of advance and recession of the Perito Moreno glacier, named MO-ACAR. Within its oscillatory behavior, in some years the glacier advances and reaches the Magellan Peninsula forming an ice-dam that break down due to the water pressure of the lake after a certain time. Thus, the main goal of the MO-ACAR model is to simulate the daily ice-front position of the glacier and the events occurrence of the ice-dam formation during 1994-2018 period. The model is calibrated and validated from an iterative optimization process, based on the maximization of correlation values and minimization of distance errors to the Magallanes Peninsula. The simulation of the ice-dam’s formation and the oscillation of the frontal position achieved high performance, reaching optimal correlation values (0.99) and small errors in the position (9.56 ± 13.94 m), respectively. The results show that glacier dynamics and ice-dam’s formation respond to different time-scales; whilst in short-, intermediate-term (daily seasonal scales), the occurrence depends as much on the characteristics of the event as on the phase and intensity of the previous event. On the contrary, in long-term periods (scales greater than one year), low-frequency modulation of the ice flow velocity, caused by variations in air temperature, controls the periods with the formation of ice-dams and free of them.

The Role of Prior Event Retrieval in Encoding Changed Event Features

When people experience everyday activities, their comprehension can be shaped by expectations that derive from similar recent experiences, which can affect the encoding of the new experience into memory. When a new experience includes changes—such as a driving route being blocked by construction—this can lead to interference in subsequent memory. However, theories based on prediction-error-driven learning propose that unpredicted changes can lead to facilitation rather than interference. One potential mechanism of effective encoding of event changes is the retrieval of related features from previous events. Another such mechanism is the generation of a prediction error when a predicted feature is contradicted. In two experiments, we tested for effects of these two mechanisms on memory for changed features in movies of everyday activities. Participants viewed movies of an actor performing everyday activities across two fictitious days. Some event features changed across the days, and some features violated viewers’ predictions. Retrieval of previous event features while viewing the second movie was associated with better subsequent memory, providing evidence for the retrieval mechanism. Contrary to our hypotheses, there was not support for the error mechanism: Prediction error was not associated with better memory when it was observed correlationally (Experiment 1) or directly manipulated (Experiment 2). These results support a key role for episodic retrieval in the encoding of new events. They also indicate boundary conditions on the role of prediction errors in driving new learning. Both findings have clear implications for theories of event memory.

The value relevance of expected vs. unexpected going concern opinions

Previous event studies find that going concern opinions (GCOs) convey significant information to the market when the audit reports appear to be unexpected. Using the value relevance method, this paper examines the differential impact of expected and unexpected going concern opinions on the market value of US firms for the 2000–2006 time period. The results suggest that while both firms receiving expected and unexpected GCOs suffer a drop in their average market value, the decrease is larger in the case of firms with unexpected GCOs. It is also observed that the market tends to shift the weight they place on earnings to the book value of equity in valuing firms with unexpected GCOs. Specifically, the decrease in the pricing multiple of earnings is larger for the case of unexpected GCOs. This result suggests that GCOs are more informative when they are unexpected. The study complements existing work by exploring whether expected GCOs have any differential valuation impact than unexpected GCOs instead of looking at the informativeness of GCOs alone.

How Things Count as the Same

How do human beings craft enduring social groups and long-lasting relationships? Given the myriad differences that divide one individual from another, why do we recognize anyone as somehow sharing a common fate with us? How do we live in harmony with groups that may not share that sense of common fate? Such relationships lie at the heart of the problems of pluralism that increasingly face so many nations today. This book answers a seemingly simple question, which forms the core of how we constitute ourselves as groups and as individuals: What counts as the same? Note that “counting as” the same differs from “being” the same. Counting as the same is thus not an empirical question about how much or how little one person shares with another or one event shares with a previous event. Nevertheless, as humans we construct sameness all the time. In the process, of course, we also construct difference. Creating sameness and difference, however, leaves us with the perennial problem of how to live with difference instead of seeing it as a threat. In this book we suggest that there are multiple ways in which we can count things as the same and that each of them fosters different kinds of group dynamics and different sets of benefits and risks for the creation of plural societies. While there might be many ways to understand how people construct sameness, three seem especially important and form the focus of our analysis: we call them memory, mimesis, and metaphor.

Adverbs of Change, Aspect, and Underspecification

Adverbs of change, such as quickly or slowly, are known to give rise to a number of interpretations. For example, Selena ran quickly says that the rate of running is high while Selena quickly noticed the plane implies that the distance between the event of noticing the plane and some previous event is short. Existing accounts (e.g. Cresswell 1978; Rawlins 2013) take rate readings as primary but struggle to derive additional interpretations. By contrast, I argue that adverbs of change measure the temporal distance between two salient events (or event parts) that are compositionally or contextually available. The main claim of the paper is that adverbs of change have a single if underspecified semantics and that the different interpretations arise through interaction with aspectual and discourse structure.

Rainfall Forecasting in Banyuwangi Using Adaptive Neuro Fuzzy Inference System

Rainfall forcasting is a non-linear forecasting process that varies according to area and strongly influenced by climate change. It is a difficult process due to complexity of rainfall trend in the previous event and the popularity of Adaptive Neuro Fuzzy Inference System (ANFIS) with hybrid learning method give high prediction for rainfall as a forecasting model. Thus, in this study we investigate the efficient membership function of ANFIS for predicting rainfall in Banyuwangi, Indonesia. The number of different membership functions that use hybrid learning method is compared. The validation process shows that 3 or 4 membership function gives minimum RMSE results that use temperature, wind speed and relative humidity as parameters.