4.6 Article

Supply chain leadership and firm performance: A meta-analysis

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.ijpe.2021.108082

Keywords

Supply chain leadership; Meta-analysis; Firm performance; Transactional leadership; Transformational leadership

Funding

  1. Natural Science Foundation of China Young Scientist Fund [71902159]
  2. Key Program Special Fund in XJTLU [KSF-A-06, KSF-A-13]

Ask authors/readers for more resources

This study conducted a meta-analysis on the relationship between supply chain leadership and firm performance, finding that supply chain leadership has a positive impact on firm performance, with transformational supply chain leadership having a more significant influence than transactional supply chain leadership. Additionally, the effect of leadership varies depending on region, industry, and performance type.
The effect of transformational vis-`a-vis transactional supply chain leadership on firm performance has been studied in the existing literature, but results remain mixed. Therefore, it is important to provide a meta-analysis literature review to investigate this relationship. In this study, 32 empirical journal articles published over the past 10 years have been reviewed and evaluated through a meta-analysis. The results reveal that supply chain leadership is positively related to firm performance; specifically, transformational supply chain leadership has a more significant influence than transactional supply chain leadership on firm performance. Further, the effect of leadership varies according to region, industry and performance type. This study provides the first meta-analysis on this relationship.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Computer Science, Theory & Methods

Towards an improved Adaboost algorithmic method for computational financial analysis

Victor Chang, Taiyu Li, Zhiyang Zeng

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING (2019)

Article Management

The impact of governmental COVID-19 measures on manufacturers' stock market valuations: The role of labor intensity and operational slack

Lujie Chen, Taiyu Li, Fu Jia, Tobias Schoenherr

Summary: This study examines the impact of the Chinese government's Level I emergency response policy on manufacturers' stock market values. The results show that the policy has a positive effect on manufacturers, but labor-intensive manufacturers experience a negative impact. Additionally, operational slack plays a positive role in maintaining business continuity for manufacturers.

JOURNAL OF OPERATIONS MANAGEMENT (2023)

Article Business

The Development of an Industry Environment for the Internet of Things: Evidence From China

Taiyu Li, Lujie Chen, Fu Jia, Ou Tang

Summary: This article examines the rapid development of the IoT industry's supply chain and its potential impact on financial risk contagion. The analysis of data from listed IoT companies in China reveals a decreasing level of financial risk contagion in the industry, indicating increasing competitiveness and resilience. The study contributes to the understanding of the coevolution theory and sheds light on the challenges and opportunities in the IoT industry.

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT (2022)

Article Engineering, Industrial

Alliance formation between a platform retailer and competing manufacturers in sharing consumer data for product development

Hiroshi Matsuhisa, Nobuo Matsubayashi

Summary: This study investigates the formation of an alliance between competing manufacturers and a monopolistic platform retailer, and analyzes the impact of the degree of differentiation among manufacturers on the formation of the alliance and the profitability of the retailer.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

A federated machine learning approach for order-level risk prediction in Supply Chain Financing

Lingxuan Kong, Ge Zheng, Alexandra Brintrup

Summary: Supply Chain Financing is used to optimize cash flows in supply networks, but recent scandals have shown inefficiencies in risk evaluation. This paper proposes a Federated Learning framework to address order-level risk evaluation.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

Examining the impact of market power discrepancy between supply chain partners on firm financial performance

Jing Gu, Xinyu Shi, Junyao Wang, Xun Xu

Summary: The asymmetric market power between a firm and its partners negatively affects the firm's financial performance. Building relationships with suppliers or customers that have matched market power is the best approach. The strength of the buyer-supplier relationship amplifies the negative impact of asymmetric market power, while the level of relationship embeddedness reduces its negative effect. Moreover, firm-specific institutional, industry, and regional economic heterogeneities also influence the financial impact of asymmetric market power.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling

Yu Du, Jun-qing Li

Summary: This study investigates the group scheduling of a distributed flexible job shop problem using the concrete precast process. The proposed solution utilizes three coordinated double deep Q-networks (DQN) as a learn-to-improve reinforcement learning approach. The algorithm shows superiority in minimizing costs and energy consumption.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

When will an overconfident entrant in the two-sided market do more good than harm?

Xiaoyu Yan, Weihua Liu, Ou Tang, Jiahe Hou

Summary: This study analyzes the market amplification effect and the impact of entrant's overconfidence on a two-sided platform. The results show that overconfident entrants can lead to price increases and benefit both the existing firms and themselves to a certain extent.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

Deep Reinforcement Learning for One-Warehouse Multi-Retailer inventory management

Illya Kaynov, Marijn van Knippenberg, Vlado Menkovski, Albert van Breemen, Willem van Jaarsveld

Summary: The One-Warehouse Multi-Retailer (OWMR) system is a typical distribution and inventory system. Previous research has focused on heuristic reordering and allocation strategies, which are time-consuming and problem-specific. This paper proposes a Deep Reinforcement Learning (DRL) algorithm for OWMR problems, which infers a multi-discrete action distribution and improves performance with a random rationing policy.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

A robust optimization approach for inventory management with limited-time discounts and service-level requirement under demand uncertainty

Yimeng Sun, Ruozhen Qiu, Minghe Sun

Summary: This study considers a multi-period inventory management problem for a retailer offering limited-time discounts and having a joint service-level requirement under demand uncertainty. It proposes a double-layer iterative approach to solve the problem and maximize total profit while balancing the service level using a posteriori method and an affinely adjustable robust chance-constrained model.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm

Anas Neumann, Adnene Hajji, Monia Rekik, Robert Pellerin

Summary: This paper presents a new mathematical formulation for planning and scheduling activities of Engineer-To-Order (ETO) projects, along with a new ETO strategy to reduce the impacts of design uncertainty. The study proposes a hybrid Layered Genetic Algorithm combined with an adaptive Lamarckian learning process (LLGA) and compares it with the branch-and-cut procedure of CPLEX. The results show good performance of the proposed mathematical model for small and medium-sized instances.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

Effects of stochastic and heterogeneous worker learning on the performance of a two-workstation production system

Thilini Ranasinghe, Chanaka D. Senanayake, Eric H. Grosse

Summary: Production systems are undergoing transformative changes, necessitating adaptability from human workers. This study developed an analytical model to account for stochastic processing times and learning heterogeneity, revealing insights into system performance.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

Digitalization & Covid-19: An institutional-contingency theoretic analysis of supply chain digitalization

Sunil Tiwari, Pankaj Sharma, Ashish Kumar Jha

Summary: Black Swan events such as the COVID-19 pandemic and the Suez Canal blockage have a significant impact on firms' technology adoption decisions, especially in terms of disruptions and digitalization in the supply chains. This study investigates the influence of institutional forces and environmental contingencies on supply chain digitalization from an institutional and contingency theory perspective. The findings emphasize the importance of organizational readiness and people readiness, including top management involvement and employee training, in facilitating digitalization.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail

Fabio Neves-Moreira, Pedro Amorim

Summary: Omnichannel retailers are using stores as distribution centers to provide faster online order fulfillment services. However, in-store picking operations can impact the offline customer experience. To address this, we propose a Dynamic In-store Picker Routing Problem (diPRP) that minimizes customer encounters while fulfilling online orders. Our solution approach combines mathematical programming and reinforcement learning to find efficient picking policies that reduce customer encounters.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Article Engineering, Industrial

How does the stakeholder exposure of vertical integration influence environmental performance?

Richard Kraude, Ram Narasimhan

Summary: In this study, the relationship between Vertical Integration (VI) and Environmental Performance (EP) is examined, revealing that highly integrated firms produce less waste but engage in fewer environmental initiatives. These findings are crucial for understanding the impact of stakeholder exposure on organizational behavior.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)

Review Engineering, Industrial

Supply chain coopetition: A review of structures, mechanisms and dynamics

Korina Katsaliaki, Sameer Kumar, Vasilis Loulos

Summary: This research conducts a systematic literature review (SLR) and content analysis on Supply Chain Coopetition (SCC) through the PRISMA framework. It examines the theory of coopetition and organizational relationships in intra-firm and inter-firm supply chains, focusing on collaboration between rival manufacturers. The study identifies structures and mechanisms of coopetition, such as buyer-supplier coopetition, supply networks coopetition, and production and distribution/logistics coopetition. It provides a holistic approach to SCC management practices and serves as a guide for future research.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2024)