Historically, infectious diseases have been the leading cause of human psychosomatic strain and death tolls. This research investigated the recent threat of COVID-19 contagion, especially its impact among frontline paramedics treating patients with COVID-19, and their perception of self-infection, which ultimately increases their agonistic behaviour. Based on the stressor–strain–outcome paradigm, a research model was proposed and investigated using survey-based data through a structured questionnaire. The results found that the perceived threat of COVID-19 contagion (emotional and cognitive threat) was positively correlated with physiological anxiety, depression, and emotional exhaustion, which led toward agonistic behaviour. Further, perceived social support was a key moderator that negatively affected the relationships between agonistic behaviour and physiological anxiety, depression, and emotional exhaustion. These findings significantly contributed to the current literature concerning COVID-19 and pandemic-related effects on human behaviour. This study also theorized the concept of human agonistic behaviour, which has key implications for future researchers.
A persistent question for information technology researchers and practitioners is how big data analytics (BDA) can improve sales performance. Therefore, this study proposed a research model to investigate the impact of BDA on perceived sales performance in accordance with the resource-based view (RBV) and dynamic capability theory. The 416 valid responses collected from the employees of pharmaceutical organizations were analyzed using structural equation modelling to test the proposed research model. Results indicated that the BDA and customer relationship management (CRM) capabilities shared a strong positive impact on perceived sales performance. BDA, as organizational resources, creates organizational dynamic capabilities, such as CRM capabilities. BDA and CRM capabilities can influence perceived sales performance. Furthermore, CRM capabilities have a significant mediating impact on the relationships between BDA and perceived sales performance. This study also highlighted the practical and theoretical implications of the proposed model, the research limitations, and the future research directions.
The excessive use of social media is an emerging phenomenon with several negative consequences in an entrepreneurial context. Based on the stressor–strain–outcome paradigm, this research aims to unveil the following: that social media late-night usage can affect two psychological strains (life invasion and technostress) among female entrepreneurs and thus influence their behavioral outcome (cognitive engagement). This study empirically tested the proposed mediation model using an online survey of 225 female entrepreneurs from the small- and medium-sized enterprise sector. A partial least squares structural equation modeling (PLS-SEM) was implemented to obtain the results. The findings indicate that late-night social media usage significantly raises life invasion and technostress among female entrepreneurs. Moreover, internal strains (life invasion and technostress) reduce female entrepreneurs’ cognitive engagement and significantly mediate the association between late-night use of social media and entrepreneurial cognitive engagement. This study draws associated practical and theoretical contributions based on findings, which were not previously discussed.
This study aims to expand the research perspective from the micro-enterprise level to the regional environment level to identify changes in the regional industrial Internet environment. The development and application of Industrial Internet technologies formed by these changes have spillover effects on Industrial Internet innovation. Sample data from 30 provinces and big cities of China from 2006 to 2018 were used to verify the network externality characteristics of industrial Internet development. The nonlinear impact of environmental factors, such as the proportion of Internet users and intellectual property protection on the open green innovation of manufacturing enterprises, was investigated through the panel threshold model. Meanwhile, the development level of the industrial Internet in eastern and western China is compared and analyzed. This study contributes to existing knowledge and guides practitioners to help manufacturing organizations develop industrial Internet environments.
Stakeholder pressure and public awareness of environmental protection drive organizations to improve environmental practices in the supply chain (SC), such as green supply chain integration (GSCI) and green innovation (GI). The use of information technology (IT) is crucial to manufacturing organizations’ GSCI and performance. However, the research on the relationship between IT capabilities, GSCI, GI and organizational performance is still limited. Therefore, empirical research is needed on the cognitive thinking of employees using IT capabilities to improve GSCI and organizational performance. The data for this study comes from SC personnel in manufacturing organizations through a structured questionnaires and was analyzed by employing structural equation modeling. Based on the results, this paper concludes that organizational IT capabilities positively affect the GSCI and improve organizational performance (environmental and operational performance). Furthermore, the study discovered that GI increases organizational performance and acts as a positive mediator in the link between GSCI and performance. The findings contribute to existing GSCI and GI knowledge, which can provide a bird’s eye-view to develop an organization’s IT capabilities to achieve competitive performance goals.
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