Purpose: Although the use of project teams is on the rise, there is a limited understanding of how project managers can ensure project team success. Research to date is relatively broad and does not pinpoint how and why leadership influences success in a project team context. Along these lines, we draw from social learning theory to illustrate that ethical leadership influences project success through leader trust and knowledge sharing.Design/methodology/approach: We collected data from 175 project team members from the information technology and software industry to evaluate our hypotheses. The results were analyzed using structural equation modeling.Findings: Our findings support our hypotheses, illustrating that ethical leadership is related to leader trust and knowledge sharing, and that leader trust and knowledge sharing mediate the relationship between ethical leadership and project success.Research limitations/implications: Our work illustrates that the behaviors inherent in ethical leadership may be particularly well-suited for these project team challenges. Ethical leaders help team members understand that project success is possible when team members are transparent with one another, discussing their goals and challenges, and then working together to ensure their actions are coordinated in a way that increases the success of the overall project.Practical implications: For those in industries or organizations where project teams are commonly used, our study may help to attract, select, and retain project managers that exhibit ethical leadership tendencies. Project managers are likely to be attracted to settings that align with their leadership style. Thus, organizations could focus on developing a culture that focuses on process over results.Originality/value: We sought to align with the contingency approach to leadership, which suggests that the ideal leadership style depends on the followers, and the context in which the leader and followers interact. Specifically, we investigate ethical leadership as an ideal approach for project managers influencing members of their project teams. Our study demonstrates how ethical leadership is an ideal, context-specific approach that project managers can apply to increase the chances of project success.

Due to recent technological developments in banking, the use of e-banking is becoming increasingly widespread. This study explored the effect of e-service quality on actual use of e-banking services and explained it through the Technology Acceptance Model. A survey was conducted in Pakistan and 493 questionnaires were collected from e-banking users and the data was analyzed using AMOS 20 and SPSS 20. The results of the study indicate that e-service quality positively affects perceived usefulness, perceived ease of use and intention to use e-banking and perceived usefulness positively affects attitude towards using e-banking and behavioral intentions to use e-banking. Perceived ease of use affects attitudes towards e-banking and attitudes positively affect behavioral intentions to use e-banking and behavioral intentions further positively affect actual use of e-banking. The sequential mediation of attitude and intention has been confirmed between e-service quality and actual use of e-banking. This study has significance for the managers of banking industry and will enable them to influence the attitude of customers in favor of their services and also help them devise strategies to improve their profitability.

Purpose: This paper aims to explore the relationship between green human resource management (GHRM) practices and the environmental performance (EP) of firms belonging to industries that may lean toward environmental pollution (e.g. oil and gas). The authors propose a holistic (serial mediation) model based on the ability-motivation-opportunity (AMO) theory and the social exchange theory (SET) and integrate organizational, i.e. perceived organizational support (POS), and individual, i.e. innovative environmental behavior (IEB), factors as explanatory mechanisms. The authors then test the model in a developing country context.Design/methodology/approach: Data were collected from white collar workers in the oil and gas industry in Pakistan. A structural equation modeling (SEM) technique and the PROCESS model 6 were used to analyze the hypothesized serial mediation model.Findings: The authors found support for the fully meditating serial mediation model. Although the direct effects of GHRM and EP were insignificant, the total effects and indirect effects through POS and IEB were significant. Similarly, the research also found support for organizational and individual factors as explanatory mechanisms in the relationship between GHRM and EP.Originality/value: This research adds to the existing literature on GHRM and the corporate EP link through proposing and testing a model of the mediating effects of POS and IEB. Furthermore, it provides empirical evidence of this model in the oil and gas sector using an Asian developing country as the context of study.

Data-driven innovations (DDI) have significantly impacted firms’ operations thanks to the massive exploitation of huge data. However, to leverage big data and achieve supply chain innovation, a variety of complementary resources are necessary. In this study, we hypothesise that supply chain innovation (SCI) is dependent on firms’ big data analytics capabilities (BAC). Furthermore, we propose that this relation is mediated by two crucial capabilities of agility and adaptability that enable firms to efficiently meet the challenges of supply chain ambidexterity. Finally, we also test the moderating role of technology uncertainty in our research model. We collected data from 386 manufacturing firms in Pakistan and tested our model using structural equation modelling. The results confirmed our initial hypotheses that agility and adaptability both mediated our baseline relationship of BAC and big data innovation in supply chains. We further found support for the moderating role of technology uncertainty. Furthermore, technology uncertainty moderates the relationship between BAC and SCI. This study extends the current literature on digital analytics capabilities and innovation along the supply chain. Practically, our research suggests that investment in big data can result in affirmative consequences, if firms cultivate capabilities to encounter supply chain ambidexterity through agility and adaptability. Accordingly, we suggest that managers belonging to manufacturing firms need to build up these internal capabilities and to monitor and assess technology uncertainty in the environment.

Drawing on dynamic capabilities and the resource-based view, we propose a conceptual model that encompasses big data analytics capabilities (BDAC), digital platform capabilities and network capabilities, supply chain innovation, and firm performance. We use the structural equation modeling to empirically validate this model on the time-lagged data of 221 micro, small, and medium enterprises (MSMEs) in the manufacturing sectors. The empirical results of our data analysis showed that BDAC significantly improved platform and networking capabilities. BDAC also improved supply chain innovation and thus financial performance. Our data indicated that networking capabilities mediated the relationships of both (a) BDAC-supply chain innovation and (b) BDAC-financial performance. Meanwhile, digital platforms mediated only the BDAC-supply chain innovation relationship. The outcomes of sequential mediation confirmed the role of both digital platform and network capabilities and supply chain innovation in the BDAC-firm performance link. Our results provide theoretical implications to operations management and offer practical insights for managers working in manufacturing MSMEs.