Purpose: Drawing on the Resource Based View (RBV) and Dynamic Capabilities Theory (DCT), the study seeks to investigate the impact of Big Data Analytics (BDA) on Project Success (PS) through Knowledge Sharing (KS) and Innovation Performance (IPF). Design/Methodology: Survey data were collected from 422 senior-level employees in IT companies, and the proposed relationships were assessed using the SMART-PLS 4 Structural Equation Modeling tool. Findings: The results show a positive and significant indirect effect of big data analytics on project success through knowledge sharing. IPF significantly mediated the relationship between BDA and PS in IT companies. Originality/Value: This study is one of the first to consider big data analytics as an essential antecedent of project success. With little or no research on the interrelationship of big data analytics, knowledge sharing, innovation performance, and organizational performance, the study investigates the mediating role of knowledge sharing and innovation performance on the relationship between BDA and PS. Implications: This study, grounded in RBV and DCT, investigates BDA’s influence on PS through KS and IPF. Implications encompass BDA’s strategic role, KS and IPF mediation, and practical and research-based insights. Findings guide BDA integration, collaborative cultures, and sustained success.
The projects of the IT industry are considered successful when they are completed within the timeline, budget, and client satisfaction on a specific project. Although client relationship is not given much importance in the delay of a project, through several studies it has been seen that the project is delayed in the IT industry due to a lack of awareness about the project to the client. The objective of this study is to inspect the impact of client relationships on project delay. Drawing on stakeholder theory and agency theory, this study investigates how client relationship influences project delay through project awareness and the role of project governance as moderator. A deductive approach of reasoning was used to test the hypotheses formulated under the current research work and proceed by using the quantitative method. This study employed a cross-sectional research design, where data was collected at a specific point in time through a survey strategy. Data was collected from the sample of 288 respondents from the IT companies of Rawalpindi and Islamabad. The data was collected using a convenience sampling technique. The demographics of the respondents were analyzed through the IBM-SPSS software program. The assumptions and the reliability of the model were also tested in SPSS. In this study, it was discovered that effective management of client relationships significantly reduces project delays, with project awareness being a crucial factor in this mitigation process. The results revealed that client relationship was negatively associated with project delay and project awareness. Whereas this linkage was mediated by project awareness. This study concludes that adequate project awareness and fruitful project governance reduce project delays and lead to positive client relationships.
This study offers a focused examination on Xinfang system, China’s unique mechanism particularly on its ability and efficacy in mediating land disputes between farmers and governmental bodies for social governance purposes. Based on interviews with 10 farmers, the study elucidates the system has low entry barriers and user-friendly, thus fast becoming the preferred system option when dealing with land conflicts. Xinfang facilitates direct communication between farmers and government officials, thereby in line with the sociocultural conventions of the rural populace. The study also highlights several constraints. While the Xinfang system employs a multifaceted approach to conflict resolution, including negotiation and grassroots governmental intervention, it lacks legislative power and institutional authority that are required for effective management of more complex or multi-stakeholder land disputes. The study advocates for a comprehensive reassessment and subsequent reform of the Xinfang system, focusing particularly on its mechanisms and procedures for dispute resolution. Such reforms are not merely instrumental for the more robust safeguarding of farmers’ land rights, but also for enhancing the overall integrity and public trust in China’s legal and administrative frameworks.
The recent development of characteristic towns has encountered a multitude of challenges and chaos. Nevertheless, there have been many instances of information asymmetry due to the absence of an effective management model and an intuitive digital management system. Consequently, this has caused the erosion of public interests and inadequate supervision by public agencies. As society is progressing at a rapid pace, there is a growing apprehension regarding poor management synergy, outdated management practices, and limited use of technology in traditional construction projects. In today's technologically sophisticated society characterized by the “Internet+” and intelligent management, there is an urgent requirement to identify a more efficient collaborative management model, thereby reducing errors caused by information asymmetry. This paper focuses on the integration of building information modeling (BIM) and integrated project delivery (IPD) for collaborative management within characteristic towns in the PPP mode. By analyzing the available literature on the application status, this study investigates the implementation methods and framework construction of collaborative management while exploring the advantages and disadvantages. On this basis, this study highlights the problems that arise and provides recommendations for improvement. Considering this, the application of the BIM-based IPD model to characteristic towns in PPP mode will enhance the effectiveness of collaborative management among all parties involved, thereby fostering an environment that facilitates decision-making and operational management in the promotion of characteristic industries.
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