International Journal of Production Economics最新文献

Understanding successful pathways for manufacturers to capture value within the service ecosystem framework is a recent and still nascent area of research that requires further investigation and growth. Within industrial settings, artificial intelligence (AI) constitutes an enabling technology that can be integrated across a network of products and systems, driving the transformation of these service ecosystems. From this perspective, this study proposes that the symbiotic convergence between AI-enabled smart manufacturing, which facilitates process and product enhancements, and servitization, which enables product availability and customization, contributes to a higher level of ecosystem value capture. To address this issue, a research model employing Smart Partial Least Squares was developed to examine the interplay between these constructs. By using survey data from a purposively selected sample of servitized manufacturing firms, the findings reveal the synergistic effects of integrating AI-enabled smart manufacturing and servitization. Furthermore, the results indicate variances across industrial sectors, and highlight that in digitally-intensive industries, service business models have undergone more substantial transformations, fostering accelerated ecosystem development streamlined by customization. Conversely, in digitally-augmented industries, where inputs are digital but products are predominantly analog, digital capabilities are primarily confined to production processes.

Motivated by the challenge of meeting carbon-conscious consumers and carbon regulations, this paper expounded on the decisions and coordination in low-carbon supply chains with a wholesale price constraint (WPC). The WPC is the behavior of large retailers (e.g., Walmart, Amazon, and E.Leclerc) that pursue a profit margin that does not fall below a certain level, which can affect supply chain operations. First, we develop a competition model, revealing that the WPC can result in a loss of total supply chain profit and a shortage in carbon emission reduction and then pose systematic challenges. Following this, we design a Nash bargaining-based cooperation model, showing that it can coordinate the supply chain and achieve a continuous allocation of optimal profits according to the bargaining power of firms. Lastly, our extended analysis incorporates the external influence of government subsidies for low-carbon technologies and designs the optimal subsidy mechanism. We demonstrate that, while government subsidies can reduce cost pressures on the supplier and provide incentives to reduce carbon emission, they can also induce the retailer to set a higher WPC for greater profitability, so the performance loss remains prominent. In this circumstance, we construct a Nash bargaining-based cooperation model that can coordinate the supply chain. Overall, our insights can help firms achieve scientific carbon emission reduction and formulate a reasonable WPC, as well as provide a quantitative basis for government carbon regulations.

Industrial symbiosis is an important practice to achieve economic and environmental advantage. This paper explores the implementation of industrial symbiosis under environmental tax policy. Specifically, we use a game-theoretic approach to analyze the interaction between the government and the manufacturers involved in industrial symbiosis in two supply chain structures: integrated structure and decentralized structure. We find that environmental tax is an effective tool to reduce the mismatch between waste supply and demand in the symbiotic supply chain. The government is inclined to set a more stringent environmental tax in the integrated supply chain, while the tax rate that triggers the full conversion of waste in decentralized scenario is larger than that in integrated scenario. The integration of the symbiotic supply chain may promote the utilization of waste and bring a higher social welfare and better environmental performance. The profit of supply chain in the integrated structure is not always higher than that in the decentralized structure. When the market potential of by-product is not large enough and the damage of waste is moderate, it is more profitable to implement industrial symbiosis in a decentralized supply chain.

In supermarkets, rapid pricing adjustments are crucial due to the short shelf life of products. Adopting a multi-case study approach, this study examines the application of dynamic pricing strategies for perishable goods through the lens of a data-driven digital transformation (DD-DT) approach. We introduce a three-phase model of DD-DT for dynamic pricing: initiation, facilitation, and strategic adaptation. In the initiation phase, we identify essential frameworks for robust data collection and analytical processes, which form the backbone of informed pricing decisions. During the facilitation phase, the study integrates sophisticated algorithms and real-time analytics to process and interpret the collected data, facilitating its seamless integration into pricing strategies. The strategic adaptation phase is critical as it focuses on the ongoing refinement and enhancement of pricing strategies, enabling supermarkets to adapt swiftly to market fluctuations and consumer behaviour changes. By presenting a comprehensive DD-DT framework, this research significantly augments the existing literature on dynamic pricing and offers actionable insights for practitioners seeking to optimize pricing strategies in a digitally transforming marketplace.

Supply chain analytics capability has recently gained more attention from both scholars and practitioners. Through the lens of information processing theory, this study examined how supply chain analytics capability impacts supply chain agility in the digital era with the associated adoption of digital technologies and platforms by companies. To obtain relevant data, a large-scale survey of Chinese manufacturing firms was conducted. Supply chain integration capability was evaluated as mediator and digital platform was evaluated as moderator. The results show that supply chain integration capability can mediate the effect of supply chain analytics capability on supply chain agility; moreover, supply chain analytics capability has a stronger impact on supply chain agility under a high level of digital platform adoption. These findings deepen the understanding of the role of supply chain analytics capability in supply chain management. This paper also provides managerial implications for enhancing supply chain agility in the digital era.

Advance selling enables consumers to order new products before their release, ensuring prompt deliveries upon release. Retailers benefit from advance selling by boosting total sales and mitigating excess or insufficient inventory costs. In practice, various advance selling policies are designed and applied. Standard Advance Selling, Advance Selling with Price Guarantee, and Advance Selling with a Deposit are often seen and successfully implemented policies by different retailers. However, given the stochastic demands and consumer valuations, whether advance selling is always desirable for retailers is unclear. If advance selling is beneficial, what are the optimal prices and ordering quantities and which policy is the best remain interesting questions. This paper aims to provide analytical solutions for optimal pricing and inventory decisions under the three advance selling policies mentioned above. The results show that the performance of the advance selling policies relies on the proportion of high-valuation consumers. The critical values of the proportion of high-valuation consumers are identified. Further, we extend the problem to consider the effects of advertising. The advertising affects the information diffusion and indirectly affects the demands of the product. Moreover, the analytical and numerical study compares the performances of different advance selling policies. Finally, multiple managerial insights are summarized.

The global manufacturing supply chain is undergoing a digital transformation (DT) powered by various digital technologies. In both stable and turbulent environments, DT helps safeguard supply chain performance by enhancing supply chain agility. While research on the use of digital technologies and their impacts on supply chains is growing, there is a lack of an overarching theoretical lens to synthesize their diverse functionalities, effects, and benefits. To address this gap, we adapt the concept of the data network effect to the supply chain context and propose that DT improves supply chain performance by enhancing supply chain resilience (SCRes) and robustness (SCRob) capabilities. To validate our hypotheses, we conducted a large-scale survey for data collection and performed Partial Least Squares Structural Equation Modelling (PLS-SEM) for data analysis. The results confirm the positive effect of DT on supply chain performance and the mediating roles of SCRob and SCRes. Our study contributes to the ongoing discussion on DT in the context of supply chains by introducing a novel theoretical perspective on the supply chain data network effect.

The literature on the antecedents of successful data-driven digital transformations needs clarity on if and how employees' cognitions and behaviours have any bearing on data-driven digital transformations with implications for operational productivity. This paper addresses this gap by drawing on socio-cognitive theory to examine how employees' cognitions (psychological safety) shape individual behaviours (employee-led process improvement) to affect organisational attainments such as data-driven digital transformations and operational productivity. A theoretical framework linking psychological safety to operational productivity through individual and serial mediations of ‘employee-led process improvement' and ‘data-driven digital transformation’ is statistically tested by collecting survey data from 183 healthcare providers in Australia. The results indicate that when employees' perceptions of interpersonal risks are allayed (psychological safety), it has a significant positive effect on operational productivity directly and indirectly through the individual and serial mediations of employee-led process improvement and data-driven digital transformations. The socio-cognitive theorisation of psychological safety as the driving mechanism that facilitates employee-led process improvement, data-driven digital transformation and operational productivity is a first in the academic literature with implications for both theory and practice.

Information technology (IT) coordination with supply chain (SC) partners improves customer and supplier integration. However, little research integrates multinational firms' cultural and geographical distance with subsidiaries' SC practice even as subsidiaries increasingly face problems engaging with their parent firms due to institutional pressures and poor SC integration. This study investigates the moderating roles of cultural and geographical distance between parent firms and subsidiaries on the relationship between subsidiaries' IT coordination with SC partners and customer and supplier integration. Three data sources were utilized to test the hypotheses. Survey data were collected from multinational firms in the retail industry across a variety of countries. Hofstede's national culture index was used to measure cultural distance, and Google Maps data were used to calculate geographical distance. We conducted structural equation modelling and hierarchical regression analysis to test the varying effects. The results indicate that when subsidiaries have higher cultural and geographical distance from their parent firms, the positive effects of IT coordination on customer and supplier integration of subsidiaries are weaker. Understanding the roles of cultural and geographical distance is important for both parent firms and subsidiaries to facilitate IT-enabled SC integration and to select the geographical locations of subsidiaries.

Green technology innovation (GTI) emerges as a critical pathway for reducing energy consumption, is crucial for semiconductor industry to address the issue of high energy consumption. Digital transformation (DT) offers opportunities to enhance GTI. There are mixed results of the relationships between DT and GTI, however, empirical studies focusing on the semiconductor industry are scant. Based on the practice-based view framework and the characteristics of Chinese semiconductor industry, we investigate how DT affects GTI. Utilizing data from 191 Chinese semiconductor firms during 2014–2022, we draw empirical evidence that DT has positive effects on GTI and the positive effects are more pronounced in non-state-owned enterprises than in state-owned enterprises. Interestingly, media coverage and executive compensation incentives weaken the positive effects. These findings advance the literatures of GTI and practice-based view and offer valuable managerial implications to enhancing GTI of Chinese semiconductor firms.