Browsing by Author "Shafique, Muhammad Noman"

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Roles of top management support and compatibility in big data predictive analytics for supply chain collaboration and supply chain performance
(Scopus, 2024-02) Shafique, Muhammad Noman; Yeo, Sook Fern; Tan, Cheng Ling
With the global digitalisation, big data has received growing attention from academicians and practitioners. However, only a few empirical studies examined the benefits of big data predictive analytics (BDPA) and its influence on supply chain collaboration (SCC) and supply chain performance (SCP). Addressing the identified gaps of the implementation of organisational information processing theory (OIPT), the current study provided the foundation to develop a conceptual framework. All relevant data were collected from 197 employees in the Chinese logistics industry. Partial least squares–structural equation modelling technique was performed. The obtained empirical results supported top management support and compatibility as critical factors for the adoption of BDPA. Moreover, BDPA exhibited positive influence on SCC and SCP. Additionally, SCC mediated the relationship between BDPA and SCP. This study presented significant theoretical contributions and provided guidelines that can benefit policymakers and organisations in the efforts of implementing BDPA for enhanced SCP. After all, improving SCP would benefit customers and the society in the case of reduction and wastage of resources.
Roles of Top Management Support and Compatibility in Big Data Predictive Analytics for Supply Chain Collaboration and Supply Chain Performance
(Elsevier, 2024-02-15) Shafique, Muhammad Noman; Yeo, Sook Fern; Tan, Cheng Ling
With the global digitalisation, big data has received growing attention from academicians and practitioners. However, only a few empirical studies examined the benefits of big data predictive analytics (BDPA) and its influence on supply chain collaboration (SCC) and supply chain performance (SCP). Addressing the identified gaps of the implementation of organisational information processing theory (OIPT), the current study provided the foundation to develop a conceptual framework. All relevant data were collected from 197 employees in the Chinese logistics industry. Partial least squares–structural equation modelling technique was performed. The obtained empirical results supported top management support and compatibility as critical factors for the adoption of BDPA. Moreover, BDPA exhibited positive influence on SCC and SCP. Additionally, SCC mediated the relationship between BDPA and SCP. This study presented significant theoretical contributions and provided guidelines that can benefit policymakers and organisations in the efforts of implementing BDPA for enhanced SCP. After all, improving SCP would benefit customers and the society in the case of reduction and wastage of resources.
Rookie Independent Directors and Agency Costs: Evidence from Chinese Listed Firms
(Elsevier, 2024-10-12) Khidmat, Waqas Bin; Ashraf, Nadia; Yeo, Sook Fern; Tan, Cheng Ling; Shafique, Muhammad Noman
This study investigates the impact of rookie independent directors (RIDs) on agency costs. Utilizing a sample of Chinese listed firms, we employ panel ordinary least square estimations. Our findings reveal that increased RIDs is positively associated with agency costs, suggesting that rookie independent directors may exacerbate agency conflicts within Chinese firms. Also, qualified financial institutional investors and gender diversity within the board composition mitigate the positive effect of RIDs on agency costs. Overall, our study contributes to understanding corporate governance dynamics in Chinese listed firms by shedding light on the nuanced relationship between rookie independent directors and agency costs.
Transforming Supply Chains:
(Daffodil International University, 2023-08) Shafique, Muhammad Noman; Rashid, Ammar; Yeo, Sook Fern; Adeel, Umar
The Sustainable Development Goals and circular economy are two critical aspects of the 2030 Agenda for Sustainable Development. They both seek to reduce the waste of natural resources and enhance society’s social, economic, and environmental goals. This study aims to identify, develop, test, and verify the significant antecedents that affect the adoption of supply chain analytics and its consequences for achieving the circular economy. We have divided the conceptual framework into two parts. In the first part, the relationship among data integration and scalability, organizational readiness, and policies and regulations as Technological–Organizational–Environmental factors as antecedents in adopting supply chain analytics. In the second part, the dynamic capabilities view grounded the relationship among supply chain analytics, supply chain integration, and sustainable supply chain flexibility effect directly and indirectly on the circular economy. Data have been collected using the survey method from 231 respondents from the manufacturing industry in Pakistan. Data have been analyzed using (i) partial least square structure equation modeling (ii) and artificial neural network approaches. The empirical findings proved that antecedents (data integrity and scalability, organizational readiness, and policy and regulation) and consequences (supply chain integration and sustainable supply chain flexibility) of supply chain analytics adoption would improve the circular economy performance. Additionally, artificial neural networks have supported these relationships. The adoption of supply chain analytics will enable organizations to supply chain integration. Additionally, organizations with more integration and analytics in their operations tend to have more flexibility and a circular economy. Moreover, organizations and society will obtain social, economic, and environmental benefits and reduce wastage and negative environmental impacts.