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The purpose of this paper is to investigate the impact of entrepreneurial orientation and total quality management on quality performance of pharmaceutical manufacturers in Pakistan. It also investigates the mediating role played by total quality management in the EO-QP relationship.

A structured questionnaire was used to collect data from 115 pharmaceutical manufacturers in Pakistan. Partial least squares structural equation modeling was used to analyze data.

The results show entrepreneurial orientation that and total quality management positively and significantly affect quality performance. Moreover, the effect of entrepreneurial orientation on quality performance is partially mediated by total quality management.

The study uses cross-sectional data. Therefore, the long-term effect of entrepreneurial orientation and total quality management on quality performance could not be determined. Moreover, quality performance has been measured based on perceptual data, which may be prone to biases, entrepreneurial orientation (EO), quality performance (QP), total quality management (TQM).

The study is unique in providing empirical evidence linking entrepreneurial orientation with quality performance through the mediating role of total quality management. Quality performance is vital in the pharmaceutical industry; thus, the study makes a valuable contribution by identifying a new mechanism to achieve it. Moreover, although both entrepreneurial orientation and total quality management are very important, only a few studies have so far investigated their interrelationship. By providing evidence from a new cultural and industrial context, the study makes a valuable contribution to an under-researched yet important area.

In the framework of Industry 4.0, the study seeks to clarify the intricate connection between modern digitalization and sustainability and the ways in which these developing technologies support sustainable practices in the societal, environmental and economic spheres. Utilizing a conceptual framework, this study integrates insights from existing literature and provides a structured investigation to explore the impact of Industry 4.0 technologies, including smart manufacturing, artificial intelligence, the internet of things (IoT) and blockchain, on sustainability. The research reveals that the integration of environmental, social, economic and human aspects of sustainability. The study emphasizes how these elements support Industry 4.0 by encouraging moral and sustainable business practices. The insights derived from this research offer practical implications for policymakers, industry leaders and researchers. By understanding the symbiotic relationship between digitalization and sustainability, stakeholders can formulate strategies that leverage new-age technologies to achieve optimal efficiency while ensuring ethical and sustainable business practices. The originality lies in the holistic approach to understanding the environmental, social and economic dimensions impacted by new-age digitalization offering a comprehensive examination of the interplay between Industry 4.0 and sustainability.

This study aims to explore the essential factors of the reason for (RF) and reason against (RA) and their impact on tourist attitudes and intentions to use e-bike sharing services by using a novel approach based on behavioral reasoning theory (BRT).

A quantitative method was used to collect data from 292 tourists and analyze the data using the partial least squares structural equation modeling (PLS-SEM) technique.

The outcomes indicate that both “RF” and “RA” are crucial in affecting tourist attitudes and intentions to use e-bike-sharing services. In addition, factors such as convenience, price saving and time saving were identified as “RF” while “RA” weather conditions, safety concerns and image barriers were identified that affect tourist attitudes and intention to use e-bike sharing services. These findings also indicate that tourists’ values of openness to change significantly influence “RF” and have no impact on “RA” and attitude toward e-bike-sharing services.

This study provides valuable insights that complement the existing literature on electric bike sharing and BRT in the context of promoting sustainable and eco-friendly consumption.

This research takes a significant step forward in investigating the tourist attitudes and intentions toward using e-bike sharing services in a tourist destination growing economy by using the BRT theory and proposing a model that considers both the “RF” and “RA” using e-bikes for urban transportation.

本研究旨在利用基于 BRT 的新方法, 探讨使用电动自行车共享服务的支持原因（RF）和反对原因（RA）的基本因素及其对游客使用电动自行车共享服务的态度和意图的影响。

采用定量方法收集 292 名游客的数据, 并使用 PLS-SEM 技术分析数据。

结果表明“RF”和“RA”对于影响游客使用电动自行车共享服务的态度和意图至关重要。此外, 方便、节省价格和节省时间等因素被确定为“RF”, 而“RA”则被确定为影响游客态度和使用电动自行车共享服务意愿的天气条件、安全问题和形象障碍。这些发现还表明, 游客对变革的开放价值观显着影响“RF”, 但对“RA”和对电动自行车共享服务的态度没有影响。

这项研究提供了宝贵的见解, 在促进可持续和环保消费的背景下补充了有关电动自行车共享和 BRT 的现有文献。

本研究利用 BRT 理论, 在调查经济增长的旅游目的地中游客对使用电动自行车共享服务的态度和意图方面迈出了重要一步, 并提出了一个同时考虑“RF”和“RA”的模型用于城市交通的电动自行车。”

Este estudio pretende explorar los factores esenciales de las razones a favor (RF) y en contra (RA) y su impacto en las actitudes e intenciones de los turistas de utilizar los servicios de bicicletas eléctricas compartidas (e-bike sharing) utilizando un enfoque novedoso basado en la BRT.

Se utilizó un método cuantitativo para recopilar datos de 292 turistas y analizarlos mediante la técnica PLS-SEM.

Los resultados indican que tanto la “RF” como la “RA” son cruciales para afectar a las actitudes e intenciones de los turistas de utilizar los servicios de e-bike-sharing. Además, se identificaron como “RF” factores como la comodidad, el ahorro de precio y el ahorro de tiempo, mientras que como “RA” se identificaron las condiciones meteorológicas, las preocupaciones por la seguridad y las barreras de imagen que afectan a las actitudes de los turistas y a su intención de utilizar los servicios de e-bike sharing. Estos resultados también indican que los valores de apertura al cambio de los turistas influyen significativamente en “RF” y no tienen ningún impacto en “RA” ni en la actitud hacia los servicios de e-bike sharing.

Este estudio aporta valiosas ideas que complementan la bibliografía existente sobre el uso compartido de bicicletas eléctricas (e-bike sharing) y el BRT en el contexto de la promoción de un consumo sostenible y respetuoso con el medio ambiente.”

Esta investigación da un importante paso adelante en la investigación de las actitudes e intenciones de los turistas hacia la utilización de los servicios de e-bike sharing en un destino turístico de economía en crecimiento utilizando la teoría del BRT y proponiendo un modelo que tiene en cuenta tanto la “RF” como la “RA” que utilizan las e-bikes para el transporte urbano.”

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.

The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.

The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.

The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.