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The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).

In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.

Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.

In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s suitability for scientific studies. The purpose of this commentary is to discuss the claims of Cadogan and Lee, correct some inaccuracies, and derive recommendations for researchers using structural equation models.

This paper uses scenario analysis to show which estimators are appropriate for reflective measurement models and composite models, and formulates the statistical model that underlies PLS Mode A. It also contrasts two different perspectives: PLS as an estimator for structural equation models vs. PLS-SEM as an overarching framework with a sui generis logic.

There are different variants of PLS, which include PLS, consistent PLS, PLSe1, PLSe2, proposed ordinal PLS and robust PLS, each of which serves a particular purpose. All of these are appropriate for scientific inquiry if applied properly. It is not PLS that subverts the realist search for truth, but some proponents of a framework called “PLS-SEM.” These proponents redefine the term “reflective measurement,” argue against the assessment of model fit and suggest that researchers could obtain “confirmation” for their model.

Researchers should be more conscious, open and respectful regarding different research paradigms.

Researchers should select a statistical model that adequately represents their theory, not necessarily a common factor model, and formulate their model explicitly. Particularly for instrumentalists, pragmatists and constructivists, the composite model appears promising. Researchers should be concerned about their estimator’s properties, not about whether it is called “PLS.” Further, researchers should critically evaluate their model, not seek confirmation or blindly believe in its value.

This paper critically appraises Cadogan and Lee (2022) and reminds researchers who wish to use structural equation modeling, particularly PLS, for their statistical analysis, of some important scientific principles.

The aim of this research is to assess the influence of the underlying service quality variable, usually related to university students' perception of the educational experience. Another aspect analysed in this work is the development of a procedure to determine which variables are more significant to assess students' satisfaction.

In order to achieve both goals, a twofold methodology was approached. In the first phase of research, an assessment of the service quality was performed with data gathered from 580 students in a process involving the adaptation of the SERVQUAL scale through a multi-objective optimization methodology. In the second phase of research, results obtained from students were compared with those obtained from the teaching staff at the university.

Results from the analysis revealed the most significant service quality dimensions from the students' viewpoint according to the scores that they provided. Comparison of the results with the teaching staff showed noticeable differences when assessing academic quality.

Significant conclusions can be drawn from the theoretical review of the empirical evidences obtained through this study helping with the practical design and implementation of quality strategies in higher education especially in regard to university education.

The purpose of this study is to critically review consumer knowledge in marketing and propose a future research agenda. Despite the many works that have examined this variable, given its strong influence on behaviour, it has generally been studied in association with other constructs, and no studies have focused on it in a specific way. Its definition, measurement and approaches to its role and usefulness are superficial and underdeveloped. After structuring and analysing the existing literature, the authors establish, (I) which aspects are of little use to the discipline, and (II) which research lines have the most potential and should be developed and studied in greater depth, to advance and complete the existing consumer knowledge framework.

A search was undertaken for documents in the main databases in which the term “consumer knowledge” appears in a marketing or consumer context, and a critical and reflexive approach was taken to analyse the main contributions and to structure them by content blocks.

Five main content blocks were identified. A set of research gaps were detected, mainly related to the lax conceptualisation of the topic, measurement problems and the scarcity of more useful works connected with business management, and several research lines are proposed that complement the existing framework to make it more complete and operational.

This paper offers a critical review and proposes a research agenda for one of the most used but little studied variables in the field of marketing, which may help academics and professionals in the discipline to continue developing useful theories and models.

El objetivo de este trabajo es revisar críticamente el conocimiento del consumidor en marketing y proponer una agenda de investigación futura. A pesar de los numerosos trabajos que han examinado esta variable, dada su fuerte influencia en el comportamiento, generalmente se ha estudiado en asociación con otros constructos, y ningún estudio se ha centrado en ella de manera específica. Su definición, medición y aproximaciones sobre su papel y utilidad son superficiales y poco desarrollados. Después de estructurar y analizar la literatura existente, establecemos (I) qué aspectos tienen poco uso para la disciplina y (II) qué líneas de investigación tienen más potencial y deben ser desarrolladas y estudiadas con mayor profundidad; para avanzar y completar el marco existente sobre conocimiento del consumidor.

Se realizó una búsqueda de documentos en las principales bases de datos en las que aparece el término “conocimiento del consumidor” en un contexto de marketing o consumo, y se adoptó un enfoque crítico y reflexivo para analizar las principales contribuciones y estructurarlas por bloques de contenido.

Se identificaron cinco bloques principales de contenido. Se detectó un conjunto de huecos de investigación, principalmente relacionados con la laxa conceptualización del tema, problemas de medición y la escasez de trabajos más útiles conectados con la gestión empresarial; y se proponen varias líneas de investigación que complementan el marco existente para hacerlo más completo y operativo.

Este documento ofrece una revisión crítica y propone una agenda de investigación para una de las variables más utilizadas pero poco estudiadas en el campo del marketing, lo que puede ayudar a académicos y profesionales en la disciplina a continuar desarrollando teorías y modelos útiles.

本文旨在对市场营销中的消费者知识进行批判性审视, 并提出未来的研究议程。虽然已有许多研究检验了该变量, 但由于其对行为产生强大影响, 通常会与其他结构变量一起研究, 而没有以特定方式专注于该变量。对其定义、测量以及其作用和用途的方法仍旧存在研究空白。通过对现有文献进行结构化分析后, 确定了以下两个方面：（I）哪些方面对该学科意义不大, （II）哪些研究方向最具研究潜力, 并且应该进一步深入发展和研究, 以推进和完善现有的消费者知识框架。

通过主要数据库检索市场营销或消费者背景下涉及“消费者知识”一词的文献, 采取批判性和反思性方法来分析其主要贡献, 并通过内容块对其进行结构化。

识别了五个主要内容块, 并发现存在一定程度的研究空白, 主要涉及该主题的概念松散化、测量问题以及与商业管理相关的有效研究的稀缺性。此外, 本文提出了几个研究线索, 这些线索为现有框架补充了信息, 使其更加完整且具备更强的操作性。

本文对市场营销领域中广泛使用但研究较少的变量进行了批判性评述, 并提出了相关研究议程。这一工作有助于学术界和专业人士继续发展实用的理论和模型。