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This study investigates the possible curvilinear relationship between operational interdependency and supply chain performance as well as the contingency effect of supply chain disruptions, in terms of disruption orientation and disruption impact.

Path analysis was employed to test the hypotheses using the data collected from Chinese manufacturers.

The results confirm an inverted U-shape effect of operational interdependency. As level of buyer-supplier operational dependency increase, the supply chain performance is enhanced. However, the benefits of operational interdependency diminish beyond a certain point. Additionally, the findings of this study show the disruption orientations positively moderate the relationship between interdependency and performance, whereas the effect of disruption impact is not significant.

The findings of this study provide an explanation to the theoretical gap about the equivocal results of the effect of dependency, which provide new insights into the literature regarding buyer-supplier relationships. Furthermore, this paper identifies the moderating role of supply chain disruption in the relationship between operational interdependency and supply chain performance, which provide further explanation about the mixed results of the effect of dependency. The results confirmed that supply chain disruption orientation positively moderate the relationship between operational interdependency and supply chain performance.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.

The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

Effective and flexible organizational models have become an avenue for driving smallholder competitiveness in the agricultural sector. However, little is understood about the processes by which resource-constrained actors deploy their organizational networks to generate and retain value in rapidly changing agrifood environments. This study examines the moderating effects of business contingencies on the interplay between organizational relationships and the resource-based performance of small-scale farmers in a developing country.

The authors propose a novel conceptual framework grounded in the relational view, netchain and contingency theories. Cross-sectional data obtained from 330 maize farmers in rural Zambia were analyzed using variance-based structural equation modeling, which involves mediation-moderation analysis.

The results show that all relational networks – vertical, horizontal and lateral – positively mediate the effects farm resources and social capital have on farmers' performance. However, these effects change depending on the predominant agency situations. Specifically, asymmetric power from customers and reputable competitors weakens the positive effect of closer horizontal relationships on business performance, while the positive effect of tighter informal vertical relationships on farmers' performance weakens under conditions of high affective trust. Moreover, the gender-based multigroup analyses highlight variations in the contingent relational view of men- and women-headed households.

The study relies on cross-sectional data from one agribusiness sector in Zambia, thus generalizations should be cautious.

The uniqueness of this study lies in the proposed theoretical framework and new empirical insights, which extend the scope of the relational view to small-scale farming households in developing countries.

The problem statement is how to identify and analyze the corporate risks involved in the relationships with external agents involved in the open product innovation process (OPIP)? Seeking to extend this investigation, the purpose of this paper is to analyze the enterprise risks identified in corporate relations with external agents of the OPIP. This study proposes the systematization of the process of identification and analysis of the enterprise risks involved in the process of open product innovation.

The case explored in this study is the OPIP of Volkswagen do Brasil (VWB), one of the most important subsidiaries of the Volkswagen Group. Criteria were selected to both assessing corporate relations with external agents of the open innovation of VWB and analyzing the enterprise risks identified in these relations. Data collection included interviews with management-level professionals engaged in the OPIP activities and technical visits to a VWB’s industrial plant.

Results demonstrate that the enterprise risks mostly affecting the OPIP have a critical impact on the manufacturing process and initial sales of the new product.

The originality of the study focuses on the proposal of a systematization of how to identify and analyze the corporate risks involved in the process of open product innovation. The study focuses on the theoretical frontier on the open innovation and enterprise risk management (ERM) in the open innovation process.