Eco-conscious behaviors have become a global imperative for entrepreneurs, as the consumer demand for products and services has become increasingly green. Hence, the purpose of this study is to identify the role of entrepreneurship education in environmental sustainability as measured by the launch of green ventures. This study also aims at extending the literature of resource-based view and flow theory by highlighting their application into the green venturing context. Data were collected from 420 Pakistani students having studied an entrepreneurship course in their university life by using the convenience sampling technique. The covariance based structural equation modeling (CB-SEM) was used to test the hypothesized relationships, and it was identified that entrepreneurship education evokes commitment to the environment, subsequently leading towards university green entrepreneurial support, environmental motivation, and green entrepreneurial behavior. University green entrepreneurial support also significantly influences green venturing; however, environmental motivation does not affect green entrepreneurial behavior. The findings of this study can be useful for policymakers in higher educational institutions, regulatory bodies, and diverse-government agencies dealing with UN sustainable development goals.

Manufacturing organizations have a pivotal role in reducing the adverse impact of global warming by adopting sustainable practices and producing environmentally-friendly products. Organizations are engaged in environmental corporate social responsibility (ECSR) and emphasize green intellectual capital (GIC), green innovative products and support for business sustainability (BUS). The current study aims to analyze the impact of organizational ECSR and GIC on green innovation (GIN) and BUS. The data for 237 participants from the manufacturing firms were analyzed via partial least square structural equation modelling (PLS-SEM). The study results revealed that ECSR and GIC are crucial for GIN and BUS. The study’s findings revealed that ECSR positively and significantly impacts green relational capital (GRC) and green structural capital (GSC). However, ECSR’s positive impact on green human capital (GHC) was insignificant. Further, the results of the mediation analysis show that GIN serves as a full mediator between GIC’s two components, GRC and GSC and a partial mediator between GHC and BUS. This study extends the environmental management literature and suggests measures for practitioners to enhance organizational capabilities in order to address environmental issues through innovative green initiatives.

A single technological advancement in the business sector tremendously changed customers’ lifestyles and consumption behavior. Drone technology is one of the main revolutions that increase business efficiency at a lower cost. However, the acceptance of emerging technologies is not rapid in developing markets. Therefore, this study aims to evaluate customers’ adoption of drone technology in the context of food delivery services. This study has used an extended technology acceptance model (TAM) to assess customers’ behavior. Product processing innovativeness, information processing innovativeness, and subjective norms have been added as additional constructs into TAM. The data of 354 customers from five different cities of Pakistan have been collected and analyzed through partial least square structural equation modeling (PLS-SEM). The results of the study revealed that all proposed hypotheses, except the positive influence of perceived ease of use on perceived usefulness, were accepted. Further, the results depict that perceived usefulness, subjective norms, and attitude were the major predictors of customers’ adoption of drone food delivery services. In addition to this, customers’ word of mouth has a greater influence and reach than other forms of marketing communication. Therefore, practitioners and marketers may consider hosting competition programs to experiment with drone food delivery systems to enhance the acceptance of this technology among the masses.

Purpose: The current study examines the impact of big data analytics capabilities (BDAC) on supply chain performances of the manufacturing firms. Based on the underpinning of resource-based view (RBV) theory, the current study will highlight the significance of BDAC on green dynamic capabilities (GDC), supply chain agility (SCA) and green competitive advantage (GCA). Furthermore, the study examines the moderating effect of supply chain innovativeness (SCI) on the relationship between GCA and firm performance (FP).Design/methodology/approach: Online survey method was employed for the data collection from the 331 managers employed in Pakistan Stock Exchange (PSX)-listed manufacturing firms. The hypothesized model was tested using partial least squares structural equation modeling (PLS-SEM) technique.Findings: The study results indicate that BDAC has a positive influence on both GDC and SCA, leading to enhanced GCA. Furthermore, the results demonstrate that GCA significantly and positively impacts FP, and the relationship between them is positively moderated by SCI.Originality/value: This study developed a novel theoretical perspective based on RBV theory and provided empirical evidence that manufacturing firms' performances are significantly influenced by BDAC, GDC and SCA. The study results provide valuable practical implications top management regarding the effectiveness of BDAC and SCA in the supply chain. The findings further highlight the significance of SCI strengthening relationship between GCA and FP.