No abstract

Technological efforts are currently being used across a broad array of industries. Through the combination of consumer choice and matching principle, the goal of this paper is to investigate the prospective implications of artificial intelligence systems on businesses’ outcomes. From an entrepreneurship standpoint, the research revealed that artificial intelligence systems can help with better decision-making. What impact does the introduction of AI-based decision-making technologies have on organizational policymaking? The quirks of human and AI-based policymaking are identified in this research based on five important contextual factors: precision of the choice search area, contribution to the innovation of the policymaking process and result, volume of the replacement collection, policymaking pace, and generalizability. We create a novel paradigm comparative analysis of conventional and automation judgment along these criteria, demonstrating how both judgment modalities can be used to improve organizational judgment efficiency. Furthermore, the research shows that, by involving internal stakeholders, they can manage the correlation among AI technologies and improve decision for businessmen. Furthermore, the research shows that customer preferences and industry norms can moderate the link between AI systems and superior entrepreneurial judgment. The goal of this work is to conduct a thorough literature analysis examining the confluence of AI and marketing philosophy, as well as construct a theoretical model that incorporates concerns based on established studies in the areas. This research shows that, in a setting with artificial intelligence systems, customer expectation, industry standards, and participative management, entrepreneurial strategic decisions are enhanced. This research provides entrepreneurs with technology means for enhancing decision-making, illustrating the limitless possibilities given by AI systems. A conceptual approach is also formed, which discusses the four factors of profit maximization: relationship of AI tools and IT with corporate objectives; AI, organizational learning, and decision-making methodology; and AI, service development, and value. This study proposes a way to exploit this innovative innovation without destroying society. We show real-world examples of each of these frameworks, indicate circumstances in which they are likely to improve decision-making performance in organizations, and provide actionable implications into their constraints. These observations have a wide variety of implications for establishing new management methods and practices from both academic and conceptual viewpoints.

El propósito del estudio fue extender el modelo SERVQUAL adicionando la actitud del cliente a las tres principales dimensiones como componentes de la medición de la calidad del servicio e investigar la influencia en la satisfacción y la lealtad de los clientes en el sector microfinanciero, específicamente de las cajas municipales de ahorro y crédito que poseen agencias en la Región Ancash, Se utilizó la técnica de la encuesta donde se recopilaron datos de 391 clientes a través del cuestionario mediante el muestreo aleatorio simple. Por tratarse de una metodología de modelos de ecuaciones estructurales (SEM) para evaluar el modelo teórico se empleó la técnica de análisis de Mínimo Cuadrado Parcial (PLS) mediante el uso del software Smart PLS 3.3.0. El hallazgo reveló que el modelo extendido tiene un impacto significativo en la satisfacción y la lealtad de los clientes en las cajas municipales de ahorro y crédito. Los coeficientes de determinación fueron; satisfacción del cliente (r2=0.637) y lealtad del cliente (r2=0.510), con un error cuadrático medio de aproximación (SRMR) de 0.06 que hace relevante el modelo confirmatorio. Además, los resultados de este estudio serán útiles para que los gerentes y los encargados de formular políticas mejoren la calidad del servicio en las cajas municipales. Se recomienda extender este estudio en otros países en vías de desarrollo, ya que se contextualizó en la realidad del sistema financiero peruano.

The main objective of a startup is to discover a suitable plan of action that can create value for growth in the economy. This research provides evidence and allied vision engrossed on three perspectives: business coaching, lean start-up approach, and innovative work behavior of women's context in solar energy entrepreneurial action. Moreover, the study is based on a quantitative method, and results indicated that it has a significant impact on the lean start-up approach on innovative work behavior and has a significant mediating effect on business coaching. This study helps researchers and practitioners cope with the entrepreneurial incubation programs for women entrepreneurs in the lean start-up approach. Moreover, this also contributes to the deep understanding of women's exploring, building, and implementing business ideas. Additionally, the study argues that guidance and directions are important for innovative entrepreneurial actions.

Environmental pollution has become the matter of concern all over the world with the increase in urbanization, transport, industrialization and several other factors. The researcher has therefore designed this study to investigate the impact of urbanization, research and development R&D expenditure, infrastructure development and real income on the emission of carbon dioxide in Asian countries. The data collection process involved six Asian countries from 1997 and ending 2019. The panel data estimation and analysis tools and techniques were applied on the collected data and the results were obtained. The results of regression estimation suggest that as per MG estimator, all the variables have significant and positive impact on CO 2 emission but infrastructure development has insignificant impact. In case of FMOLS, again all the variables have significant and positive impact on CO 2 emission but infrastructure development has insignificant impact. However, in case of DOLS, all the variables have shown significant impact on CO 2 emission. In the last, DK estimator indicates that urbanization, real income and population density have significant and positive impact on CO 2 emission but R&D expenditure and infrastructure development has insignificant impact. In this way, the impacts of all independent and control variables on CO 2 emission were estimated.

Information and communication technologies have had a significant impact on people's quality of life in recent years. But, its educational potential has yet to be fully realized. In the wake of the covid-19 outbreak, this article presents an examination of the digital competence of university professors. The development of these talents among university professors was studied. To collect data, Google Forms was used to create online surveys. Requests were sent to the 240 professors of the Universidad Nacional Santiago Antunez de Mayolo via institutional email, and the responses of the 187 professors were included in the SPSS V26 database as a result of the outbreak. The findings show that university professors have sufficient digital skills, but their use in non-face-to-face classrooms is restricted, requiring a review of training programs in public institutions in this context of the COVID-19 epidemic. Las tecnologías de la información y la comunicación han tenido un impacto significativo en la calidad de vida de las personas en los últimos años. Pero, su potencial educativo aún no se ha realizado plenamente. A raíz del brote de covid-19, en este artículo se presenta un examen de la competencia digital de los profesores universitarios. Se estudió el desarrollo de estos talentos entre los profesores universitarios. Para recopilar datos, se utilizó Google Forms para crear encuestas en línea. Se enviaron solicitudes a los 240 profesores de la Universidad Nacional Santiago Antunez de Mayolo a través del correo electrónico institucional, y las respuestas de los 187 profesores se incluyeron en la base de datos SPSS V26 como resultado del brote. Los hallazgos muestran que los profesores universitarios tienen suficientes habilidades digitales, pero su uso en aulas no presenciales está restringido, lo que requiere una revisión de los programas de capacitación en instituciones públicas en este contexto de epidemia de COVID-19

Business development is dependent on a well-structured human resources (HR) system that maximizes the efficiency of an organization’s human resources input and output. It is tough to provide adequate instructions for HR’s unique task. In a time when the domestic labor market is still maturing, it is difficult for companies to make successful adjustments in HR structures to meet fluctuations in demand for human resources caused by shifting corporate strategies, operations, and size. Data on corporate human resources are often insufficient or inaccurate, which creates substantial nonlinearity and uncertainty when attempting to predict staffing needs, since human resource demand is influenced by numerous variables. The aim of this research is to predict the human resource demand using novel methods. Recurrent neural networks (RNNs) and grey wolf optimization (GWO) are used in this study to develop a new quantitative forecasting method for HR demand prediction. Initially, we collect the dataset and preprocess using normalization. The features are extracted using principal component analysis (PCA) and the proposed RNN with GWO effectively predicts the needs of HR. Moreover, organizations may be able to estimate personnel demand based on current circumstances, making forecasting more relevant and adaptive and enabling enterprises to accomplish their objectives via efficient human resource planning.

This study investigates how environmental awareness of suppliers affects the distribution of products and services and management performance of environmental data using three key indicators: MPI (Management Performance Indicator), OPI (Operational Indicator Index), ECI (Environmental Condition Indicator). In order to prove these relations, the research models and hypotheses were established. After collecting 295 samples of effective responses from suppliers, an experimental analysis was conducted using structural equation modeling. The main findings reveals that the environmental awareness of suppliers influence the distribution and the representation of environmental data to the management with mediating effect on the relationship between suppliers and environment. This study has important significances: an academic one, that the scope of environmental awareness was extended from the consumer to the organizational perspective, especially to suppliers; another practical due that it has increased environmental awareness of suppliers improving the environmental management performance; and also, an educational with positive implications for the dissemination of environmental information.