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Departing from conflicting findings on the role of involvement in the formation of the consideration set, the authors of this study seek to shed light to the wine consumer behaviour and expand previous findings in the bring-your-own-bottle (BYOB) of wine restaurant industry. The authors seek to determine the contradictory effect of involvement on the consideration set size and variety.

Three empirical studies were conducted. In Study 1, the relationships were tested in a personal consumption situation and in Study 2 in a gift-giving context. Finally, in Study 3, inconsistencies in the intensity of the hypothesised relationships were explored by testing the triple interaction amongst the three variables (i.e. involvement, decision-making context and decision domain).

According to the authors' findings BYOB of wine consumers form larger considerations sets in memory-based decision contexts. Involvement's effect on wine consideration set size is stronger in memory-based decisions. BYOB restaurant patrons form smaller sets of alternatives for personal consumption. BYOB restaurant patrons form more heterogeneous sets of alternatives in wine gift-giving. BYOB of wine restaurants should facilitate consumers' wine-selection process.

The authors make an effort to explain and determine the up-to-date contradictory effect of restaurant patrons' involvement on the BYOB of wine consideration set size and the amount of variety contained therein. The study offers new insights, by unfolding the moderating effect of decision-making contexts (i.e. memory-based versus stimuli-based) and decision domains (i.e. personal consumption versus gift-giving) on this effect of involvement on the properties of consideration sets.

This paper aims to present the results of the comparison between different approaches to the prediction of electricity prices. It is well-known that the properties of the data generation process may prefer some modeling methods over the others. The data having an origin in social or market processes are characterized by unexpectedly wide realization space resulting in the existence of the long tails in the probabilistic density function. These data may not be easy in time series prediction using standard approaches based on the normal distribution assumptions. The electricity prices on the deregulated market fall into this category.

The paper presents alternative approaches, i.e. memory-based prediction and fractal approach compared with established nonlinear method of neural networks. The appropriate interpretation of results is supported with the statistical data analysis and data conditioning. These algorithms have been applied to the problem of the energy price prediction on the deregulated electricity market with data from Polish and Austrian energy stock exchanges.

The first outcome of the analysis is that there are several situations in the task of time series prediction, when standard modeling approach based on the assumption that each change is independent of the last following random Gaussian bell pattern may not be a true. In this paper, such a case was considered: price data from energy markets. Electricity prices data are biased by the human nature. It is shown that more relevant for data properties was Cauchy probabilistic distribution. Results have shown that alternative approaches may be used and prediction for both data memory-based approach resulted in the best performance.

“Personalization” of the model is crucial aspect in the whole methodology. All available knowledge should be used on the forecasted phenomenon and incorporate it into the model. In case of the memory-based modeling, it is a specific design of the history searching routine that uses the understanding of the process features. Importance should shift toward methodology structure design and algorithm customization and then to parameter estimation. Such modeling approach may be more descriptive for the user enabling understanding of the process and further iterative improvement in a continuous striving for perfection.

Memory-based modeling can be practically applied. These models have large potential that is worth to be exploited. One disadvantage of this modeling approach is large calculation effort connected with a need of constant evaluation of large data sets. It was shown that a graphics processing unit (GPU) approach through parallel calculation on the graphical cards can improve it dramatically.

The modeling of the electricity prices has big impact of the daily operation of the electricity traders and distributors. From one side, appropriate modeling can improve performance mitigating risks associated with the process. Thus, the end users should receive higher quality of services ultimately with lower prices and minimized risk of the energy loss incidents.

The use of the alternative approaches, such as memory-based reasoning or fractals, is very rare in the field of the electricity price forecasting. Thus, it gives a new impact for further research enabling development of better solutions incorporating all available process knowledge and customized hybrid algorithms.

Extant research has largely treated country image (CI) as an exogenous variable, focusing mostly on its consequences for consumers’ evaluations and purchases of products or brands originating from a country. Scant research has examined the instrumental role of a country’s brands and products in the evaluations of CI. This study aims to investigate how the brands of a country contribute to CI ratings and the conditions underlying their effect on CI.

Three experimental studies test the hypotheses, one pertaining to the effect of brands on CI (N = 227), the second to the effect of products on CI (N = 116) and the third to the effect of brands and products on industry image (N = 215). The experimental approach overcomes the limitations of cross-sectional surveys commonly used in CI studies to detect the direction of the observed effects. Furthermore, respondents (British consumers) were allowed to determine the brands and products associated with a country.

Drawing on memory schema theory, across three studies, the authors identify two types of reverse inferences: from brand to CI and from product category to CI. The reverse inference from a brand to a superordinate image is stronger for industry image than for CI.

This research focuses on consumers’ evaluations from only one country (the UK). Further research could replicate the studies across different countries and with different countries of origin (COOs). Researchers could also examine the influence of brands misidentified with the wrong COO and mistakenly stored as such in consumers’ memories.

The results are relevant for managers and consultants working with country- (place-) branding campaigns. Brands and industries can help strengthen the evaluations of the economic dimension of different countries; however, these assets are underdeveloped in country-branding campaigns. Linking countries with brands and industries in campaigns could result in positive associations, which, in turn, could enhance the reputational rating of the countries.

This research extends previous studies on the effects of a country’s products and brands on CI by incorporating the mediating role of industry image between brands/products and CI, separating the effects of brand and product category on CI, allowing consumers to determine, which brands and products are associated with a country and adopting an experimental methodology to ascertain the causal direction of the effects.

This research seeks to examine the influence of sponsorship on spectators' consideration sets by investigating, in a naturalistic setting, whether sport sponsorship adds a prominent brand to spectators' consideration sets, with and without the explicit memory that the brand is a sponsor.

A field study involved 1,084 visitors to a tennis tournament. For the control group (n=276), the interviews took place before the spectators entered the stadium; interviews with the exposed group (n=808) were conducted after they had attended at least one match. Three hypotheses related to consumer status and consideration set conditions were tested.

Sponsorship can influence the likelihood that a prominent brand becomes part of the consideration set in a naturalistic setting, even without an explicit memory that the brand is a sponsor. This implicit sponsorship effect was limited to the memory-based consideration set of non-consumers of the brand.

This study establishes an implicit sponsorship effect for prominent brands in naturalistic environments and contributes to a better understanding of moderating (boundary) conditions.

This paper aims to present a single-block memory-based FFT processor design with a conflict-free addressing scheme for field-programmable gate arrays FPGAs with dual-port block memories. This study aims for a single-block dual-port memory-based N-point radix-2 FFT design that uses memory locations and spending minimum clock cycle.

A new memory-based Fast Fourier Transform (FFT) design that uses a dual-port memory block is proposed. Dual-port memory allows the design to perform two memory reads and writes in a single clock cycle. This approach achieves low operational clock and smallest memory simultaneously, excluding some small overhead for exceptional address changes. The methodology is to read from while writing to a memory location, eliminating the need for excess memory and additional clock cycles.

With the minimum memory size and the simplest architecture, radix-2 FFT and single-memory block are used. The number of clock pulses spent for all FFT operations does not provide much advantage for low-point FFT operations but is important for high-point FFT operations. With the developed algorithm, N memory is used, and the number of clock pulses spent for all FFT stages is (N/2 +1)log2N for all FFT operations.

This is an original paper, which has simultaneously in whole or in part been submitted anywhere else.

In this commentary, the authors follow DeNisi and Sockbeson’s suggestions to reintegrate the organizational feedback and feedback-seeking literatures. They build on and extend their theorizing by suggesting a framework of simultaneous dual judgment processing in both feedback-seeking and organizational feedback interventions..

In the model, evaluation salience plays a role in how performance information is stored (i.e. as online judgments or loose memories), and rater motivation will determine to what extent the rater will deliberately use the stored information to give feedback.

The authors clarify some of the implications of the model for the accuracy of the feedback given, as well as how the cognitive methods that are used can be one of the explaining mechanisms in the link between feedback and performance.

This dual judgment processing approach accounts for the true complexity of the process of organizational feedback that has been largely ignored in past research.

En este comentario seguimos las sugerencias de DeNIsis y Sockbeson de reintegrar las literaturas de feedback organizativo y feedback buscado. Tomando como punto de partida su trabajo lo extendemos para sugerir un marco de procesamiento dual del juicio en las intervenciones tanto de feedback organizativo como de feedback buscado.

En nuestro modelo, la prominencia de la evaluación juega un importante papel sobre cómo se almacena la información sobre el rendimiento (i.e. como juicios online o como recuerdos vagos), y la motivación del evaluador determina hasta qué punto éste usará deliberadamente la información almacenada para proporcionar feedback.

Clarificamos algunas de las implicaciones de nuestro modelo para la precisión del feedback ofrecido, e indicamos como el modo en el que los métodos cognitivos se usan puede ser uno de los mecanismos que explican la relación entre el feedback y el rendimiento.

Esta aproximación dual del juicio toma en consideración la verdadera complejidad del proceso de feedback organizativo que ha sido ignorada en trabajos anteriores.

Procesamiento dual del juicio, Feedback, Evaluación del rendimiento, Búsqueda de feedback, Procesos de feedback, Sesgos

Papel Conceptual

Neste comentário, seguimos as sugestões de DeNIsis e Sockbeson para reintegrar as literaturas de feedback organizacional e feedback procurado. Tomando como ponto de partida este trabalho, nós o estendemos para sugerir uma estrutura de processamento dual do julgamento nas intervenções tanto do feedback organizacional quanto do feedback procurado.

Em nosso modelo, a proeminência da avaliação desempenha um papel importante na forma como as informações sobre o desempenho são armazenadas (ou seja, julgamentos online ou memórias vagas), e a motivação do avaliador determina até que ponto ele usará deliberadamente as informações armazenadas para fornecer feedback.

Esclarecemos algumas das implicações de nosso modelo para a precisão do feedback oferecido e indicamos como a maneira pela qual os métodos cognitivos são usados pode ser um dos mecanismos que explicam a relação entre feedback e desempenho.

Esta abordagem dual do julgamento leva em conta a verdadeira complexidade do processo de feedback organizacional que foi ignorado em trabalhos anteriores.

Processamento de julgamento dual, Feedback, Avaliação de desempenho, Procura de feedback, Processos de feedback, Viés

Papel conceitual

As main mode of modern service industry and future economy society, the research on crowd network can greatly facilitate governances of economy society and make it more efficient, humane, sustainable and at the same time avoid disorders. However, because most results cannot be observed in real world, the research of crowd network cannot follow a traditional way. Simulation is the main means to put forward related research studies. Compared with other large-scale interactive simulations, simulation for crowd network has challenges of dynamic, diversification and massive participants. Fortunately, known as the most famous and widely accepted standard, high level architecture (HLA) has been widely used in large-scale simulations. But when it comes to crowd network, HLA has shortcomings like fixed federation, limited scale and agreement outside the software system.

This paper proposes a novel reflective memory-based framework for crowd network simulations. The proposed framework adopts a two-level federation-based architecture, which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem.

With reference to HLA, this paper proposes a novel reflective memory-based framework toward crowd network simulations. The proposed framework adopts a two-level federation-based architecture, system-level simulation (system federation) and application-level simulation (application federations), which separates simulation-related environments into physical and logical aspect to enhance the flexibility of simulations. Simulation definition is introduced in this architecture to resolve the problem of outside agreements and share resources pool (constructed by reflective memory) is used to address the systemic emergence and scale problem.

Simulation syntax and semantic are all settled under this framework by templates, especially interface templates, as simulations are separated by two-level federations, physical and logical simulation environment are considered separately; the definition of simulation execution is flexible. When developing new simulations, recompile is not necessary, which can acquire much more reusability, because reflective memory is adopted as share memory within given simulation execution in this framework; population can be perceived by all federates, which greatly enhances the scalability of this kind of simulations; communication efficiency and capability has greatly improved by this share memory-based framework.

This is the first part of a two-part paper. The purpose of this paper is to report on methods that use the Response Surface Methodology (RSM) to investigate an Evolutionary Algorithm (EA) and memory-based approach referred to as McBAR – the Mapping of Task IDs for Centroid-Based Adaptation with Random Immigrants. Some of the methods are useful for investigating the performance (solution-search abilities) of techniques (comprised of McBAR and other selected EA-based techniques) for solving some multi-objective dynamic resource-constrained project scheduling problems with time-varying number of tasks.

The RSM is applied to: determine some EA parameters of the techniques, develop models of the performance of each technique, legitimize some algorithmic components of McBAR, manifest the relative performance of McBAR over the other techniques and determine the resiliency of McBAR against changes in the environment.

The results of applying the methods are explored in the second part of this work.

The models are composite and characterize an EA memory-based technique. Further, the resiliency of techniques is determined by applying Lagrange optimization that involves the models.

This study is part of a series aimed at improving the city's environment, as fully restoring the past soundscape is hardly feasible. The initial study aims to uncover the city's sound characteristics, including iconic sounds that have shaped the city's environment for decades, contributing to its status as Indonesia's second most popular tourist destination. This stage is critical for informing policymaking to carefully manage and enhance the urban acoustic environment in alignment with the preserved culture.

The city's sound profile was examined using standard urban sound taxonomies. The study used quantitative methods, including (1) sound pressure level (SPL) measurements and sound recordings, (2) in situ surveys and (3) memory-based surveys. The first set of data were compared to current standards and standard urban sound taxonomies, while the second set was analysed to determine the median rating score for determining the soundscape dimensions. The third data set was used to identify the specific acoustic aspects inherent in Yogyakarta.

Yogyakarta's acoustic environment was bustling, with traffic noise and human activities dominating the soundscape, surpassing the standard levels. Many sounds not classified in standard urban sound taxonomies were present, showing the diverse nature of urban sound classification, particularly in a cultural and traditional city like Yogyakarta. The memory-based survey unveils Yogyakarta's two most remarkable soundmarks, “gamelan” and “andong”, which support the findings of prior studies. The in situ survey rated the city's acoustic environment as eventful, pleasurable and generally appropriate, emphasising the presence of cultural sounds unique to Yogyakarta, even though they are not fully audible in the current environment.

The standard sound taxonomies used in urban areas need to be adjusted to include the unique sounds produced by cultural and traditional activities in developing countries. The ordinates and subordinates of the taxonomies also need to be updated. When cultural and daily activities are massively seen in a particular city, the sounds they produce can be recalled exclusively as the city's signature. It is urgent to implement policies to safeguard the few remaining soundmarks before they disappear entirely.

This is the second part of a two-part paper. The purpose of this paper is to report the results on the application of the methods that use the Response Surface Methodology to investigate an evolutionary algorithm (EA) and memory-based approach referred to as McBAR – the Mapping of Task IDs for Centroid-Based Adaptation with Random Immigrants.

The methods applied in this paper are fully explained in the first part. They are utilized to investigate the performances (ability to determine solutions to problems) of techniques composed of McBAR and some EA-based techniques for solving some multi-objective dynamic resource-constrained project scheduling problems with a variable number of tasks.

The main results include the following: first, some algorithmic components of McBAR are legitimate; second, the performance of McBAR is generally superior to those of the other techniques after increase in the number of tasks in each of the above-mentioned problems; and third, McBAR has the most resilient performance among the techniques against changes in the environment that set the problems.

This paper is novel for investigating the enumerated results.