Adnan Abbas

Purpose: Although Chinese manufacturing firms are increasing investments in artificial intelligence (AI), evidence remains limited on how the intensity of AI use creates sustainable competitiveness. Drawing on the resource-based view and dynamic capabilities theory, this study examines the direct and indirect effects of AI adoption intensity on sustainable competitiveness through information visibility and operational resilience and evaluates the contingent role of AI-informed decision capability. Design/methodology/approach: Survey data from 423 managers and operational employees in Chinese manufacturing firms were analyzed using partial least squares structural equation modelling with 5,000 bootstrap resamples and necessary condition analysis. Findings: AI adoption intensity positively affects information visibility, operational resilience, and sustainable competitiveness. Information visibility enhances resilience and competitiveness, and resilience improves competitiveness. Information visibility mediates the effects of AI adoption intensity on resilience and competitiveness, while resilience mediates the effect if AI adoption intensity on competitiveness. AI-informed decision capability strengthens only the relationship between AI adoption intensity and sustainable competitiveness. Practical implications: Managers should embed AI across core processes while strengthening information-sharing routines, resilience practices, and managers' ability to interpret AI outputs. Originality/value: The study conceptualizes AI adoption intensity as a strategic resource and identifies information visibility and operational resilience as the capability pathways through which AI-enabled manufacturing firms build sustainable competitiveness.

Purpose: Despite rising digital investments, manufacturers in emerging economies struggle to convert explorative IT capabilities into better performance, especially under environmental regulations. This research, grounded in Ambidexterity Theory, examines how explorative IT capabilities boost performance via green innovation in Pakistan's manufacturing sector. Design/methodology/approach: The study employs multi-analytical methods, including partial least squares structural equation modeling, necessary condition analysis and importance-performance map analysis, to test the hypothesis among 620 respondents using survey data. Findings: Findings show that explorative IT capability boosts organizational performance via green innovation, strengthened by environmental regulations. Analyses identify necessary and performance-enhancing capabilities. Originality/value: This paper explains how explorative digital capabilities drive sustainability outcomes in manufacturing. Using sufficiency- and necessity-based methods, it offers a decision-focused view that guides managers to invest in the most impactful digital capabilities for maximum returns.

Corrigendum: Organizational Behavior in Green Supply Chain Integration: Nexus Between Information Technology Capability, Green Innovation, and Organizational Performance

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.

This study aims to evaluate the performance of the Chinese healthcare system. It uses sustainable development goal (SDG) 3, set by the United Nations to ensure healthy lives and promote well-being for all at all ages as a benchmark. It uses data of 17 variables ranging from the year 2000 to 2017 and uses a multistage methodology to evaluate the performance. In the first stage, it uses difference in mean test to know whether or not the indicators show an improvement in the second decade of the 21st century compared to the first decade. In the second phase, simple linear regression has been used to know the rate of change of performance of every indicator over the sample period. The third step compares the performance of the healthcare sector with the sustainable goals set by the UN and the fourth phase attempts to forecast performance for the next five years i.e., 2018 to 2022. As per the results, the Chinese healthcare sector has performed very well on many fronts except alcohol consumption in males, road accidents and the incidence of non-communicable diseases. Alcohol consumption by males is touching dangerous levels. Therefore, the policies should focus on educating males to lower their alcohol consumption to stay fit and healthy.

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.