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To most people, money is a motivator, which is robustly true for salespeople. A high love of money attitude predicts university students’ poor academic performance in a business course and cheating in laboratory experiments and multiple panel studies, but money (income) itself does not predict dishonesty. Extrinsic reward undermines intrinsic motivation. Very little research has incorporated the grit construct in the sales literature and explored the relationship between grit and the love of money. Further, a growth mindset and a fixed mindset may also impact salespeople’s job performance. This study aims to explore a brand-new theoretical structural equation model (SEM) and investigate the relationships between individual characteristics (growth and fixed mindsets and grit orientation) and job performance directly and indirectly through a mediator – salespeople’s love of money attitude.

This study uses Qualtrics and collects data from 330 business-to-business (B2B) salespeople across several industries in the USA. This study uses a formative SEM model to test this study’s hypotheses.

First, there are significant correlations among grit, a growth mindset and a fixed mindset, revealing no construct duplication or redundancy. Second, both a growth mindset and grit indirectly enhance job performance through the love of money attitude – a mediator, offering a brand-new discovery. Third, counter-intuitively, a growth mindset and grit do not directly improve job performance. Fourth, grit is significantly and negatively related to the love of money attitude, adding a new twist to this study’s theoretical model. Fifth, a fixed mindset undermines job performance directly but is unrelated to the love of money. Overall, B2B salespeople’s love of money attitude (employee demand) undermines sales personnel’s self-reported job performance (organization demand) in the organization and employee’s supply and demand exchange relationship.

The findings reveal that a growth mindset, a fixed mindset and grit contribute differently to sales personnel’s love of money attitude and job performance in this study’s theoretical model. The love of money serves as a mediator. A commonly accepted belief is that money is a motivator. Money (income) itself and the love of money attitude are two separate constructs. This study’s novel discoveries provide the essential missing monetary-aspirations-to-job-performance link in the literature – ardent monetary aspiration undermines self-reported job performance. This study offers inspiration to help decision-makers make happy, healthy and wealthy decisions and improve performance.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

This research aims to empirically investigate the impacts of product and international diversification strategies on firm-level inventory performance.

This study empirically examines the associations between product and international diversification strategies and inventory performance based on a sample of 64,124 observations across 7,367 US publicly traded firms between 1989 and 2019 from the COMPUSTAT Segment, Fundamental Annual and Fundamental Quarterly data files. We employ both linear and nonlinear regression models to perform our empirical analysis.

This research provides strong evidence that there exists a U-shaped relationship between unrelated product diversification and inventory level and a partially inverted U-shaped relationship between international diversification and inventory level. We also find a positive impact of related product diversification on inventory level, but there is no significant curvilinear relationship between related product diversification and inventory level.

Our research findings offer important insights into top management’s strategic planning for diversification strategies and operations manager’s inventory control policies to achieve the strategic fit between corporate diversification and inventory management.

Product and international diversification strategies not only play an essential role in the firm’s competitive advantage, but also have a significant influence on operations manager’s inventory decision. This research is among the first to systematically investigate how top management’s related product, unrelated product and international diversification strategies may have complex nonlinear impacts on inventory performance.

This study aims to analyze and discuss the impact of corporate social responsibility (CSR) on firms’ performance, as well as to examine the interplay between CSR and the economy, society and innovation.

This paper collects data from 420 manufacturing firms across various geographical regions in China. By using a structural equation model, the paper investigates the impact of CSR on enterprise innovation, customer management capability, market competitiveness (MC) and firm financial performance.

The findings demonstrate that CSR performance positively contributes to enhancing the level of enterprise innovation, as well as customer management capability and market competitiveness. Furthermore, it assists enterprises in improving market competitiveness and elevating customer management capabilities. Thus, CSR can have a positive effect on the firm financial performance.

The outcomes presented in this paper offer valuable evidence regarding the influence of implementing CSR on different aspects of enterprise performance and innovation. Moreover, it provides practical recommendations for enterprises seeking to transition towards low-carbon practices and upgrade their manufacturing industry.

The purpose of this paper is to empirically analyze the impact of directors’ and officers’ (D&O) liability insurance on enterprise strategic change. It also explores the mediating role of litigation risk, the moderating roles of enterprise science and technology level and precipitation organizational slack between them. In addition, it examines the joint moderating roles of the top management team (TMT) external social network and enterprise science and technology level, and enterprise scale and precipitation organizational slack.

Using the unbalanced panel data of A-share listed companies in the Shanghai and Shenzhen stock exchanges of China from 2002 to 2020 as the research sample, this paper uses the ordinary least square method and fixed-effect model to study the relationship between D&O liability insurance and enterprise strategic change. The study also focuses on the mediating mechanism and moderating mechanisms between them.

The authors find that D&O liability insurance has an “incentive effect,” which can significantly promote enterprise strategic change. Litigation risk plays a partial mediating role between D&O liability insurance and enterprise strategic change. Enterprise science and technology level and precipitation organizational slack negatively moderate the relationship between D&O liability insurance and enterprise strategic change. TMT external social network and enterprise science and technology level, and enterprise-scale and precipitation organizational slack have joint moderating effects on the relationship between D&O liability insurance and enterprise strategic change.

This paper confirms the “incentive effect hypothesis” of the impact of D&O liability insurance on enterprise strategic change, which not only broadens the research perspective of enterprise strategic management but also further expands the research scope of D&O liability insurance. Besides, this paper thoroughly explores the influencing mechanisms between D&O liability insurance and enterprise strategic change, providing incremental contributions to the research literature in the field of enterprise risk management and corporate governance. The findings have practical guiding significance for expanding the coverage of D&O liability insurance, promoting the implementation of strategic changes and improving the level of corporate governance of Chinese enterprises.

In this research, we explore the adverse impact of foreign ownership on operational security, a critical operational implication of the liability of foreignness (LOF).

The empirical analysis is based on a multi-country dataset from the World Bank Enterprises Survey, which contains detailed firm-level information from over 8,902 firms in 82 emerging market countries. We perform a series of robustness checks to further confirm our findings.

We find that a high ratio of foreign ownership is associated with an increased likelihood of security breaches and higher security costs. Our results also indicate that high levels of host countries’ institutional quality and firms’ local embeddedness can mitigate such vulnerability in operational security.

This study is one of the first to uncover the critical operational implication of the LOF, indicating that a high ratio of foreign ownership exposes firms to operational security challenges.

Given the lack of focus on a standardized measurement framework (e.g. benchmarking tool) to assess and quantify complexity within the supply chain, this study has developed a unified supply chain complexity (SCC) index and validated its utility by examining the relationship with firm performance. More importantly, it examines the role of firm owners' business knowledge, sales strategy and board management on the relationship between SCC and firm performance.

In this study, the unit of analysis is Indian manufacturing companies listed on the Bombay Stock Exchange (BSE). This research has merged panel data from two secondary data sources: Bloomberg and Prowess and empirically operationalized five key SCC drivers, namely, number of suppliers, the number of supplier countries, the number of products, the number of plants and the number of customers. The study employs panel data regression analyses to examine the proposed conceptual model and associated hypotheses. Moreover, the present study employs models that incorporate robust standard errors to account for heteroscedasticity.

The results show that complexity has a negative and significant effect on firm performance. Further, the study reveals that an owner's business knowledge and the firm's effective sales strategy and board management can significantly lessen the negative effect of SCC.

This study develops an SCC index and validates its utility. Also, it presents a novel idea to operationalize the measure for SCC characteristics using secondary databases like Prowess and Bloomberg.

The proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.

A total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.

Results indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.

This study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505

Based on the strong feature representation ability of the convolutional neural network (CNN), generous object detection methods in remote sensing (RS) have been proposed one after another. However, due to the large variation in scale and the omission of relevant relationships between objects, there are still great challenges for object detection in RS. Most object detection methods fail to take the difficulties of detecting small and medium-sized objects and global context into account. Moreover, inference time and lightness are also major pain points in the field of RS.

To alleviate the aforementioned problems, this study proposes a novel method for object detection in RS, which is called lightweight object detection with a multi-receptive field and long-range dependency in RS images (MFLD). The multi-receptive field extraction (MRFE) and long-range dependency information extraction (LDIE) modules are put forward.

To concentrate on the variability of objects in RS, MRFE effectively expands the receptive field by a combination of atrous separable convolutions with different dilated rates. Considering the shortcomings of CNN in extracting global information, LDIE is designed to capture the relationships between objects. Extensive experiments over public datasets in RS images demonstrate that our MFLD method surpasses the state-of-the-art methods. Most of all, on the NWPU VHR-10 dataset, our MFLD method achieves 94.6% mean average precision with 4.08 M model volume.

This paper proposed a method called lightweight object detection with multi-receptive field and long-range dependency in RS images.