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Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

Blockchain is a distributed ledger technology that uses cryptography to ensure transmission and access security, which provides solutions to numerous challenges to complex supply networks. The purpose of this paper is to empirically test the impact of blockchain implementation on shareholder value varying from internal and external complexity from the complex adaptive systems (CASs) perspective. It further explores how business diversification, supply chain (SC) concentration and environmental complexity affect the relationship between blockchain implementation and shareholder value.

Based on 138 blockchain implementation announcements of listed companies on the Chinese A-share stock market, the authors use event study methodology to evaluate the impact of blockchain implementation on shareholder value.

The results show that blockchain implementation has a positive impact on shareholder value, and this impact will be moderated by business diversification, SC concentration and environmental complexity. In addition, environmental complexity exerts a moderating effect on SC concentration. In the post hoc analysis, the authors further explore the impact of blockchain implementation on long-term operational performance.

This is the first research empirically examining the effect of blockchain implementation on shareholder value varying from internal and external complexity from the CASs perspective. This paper provides evidence of the different effects of blockchain implementation on short- and long-term performance. It adds to the interdisciplinary research of information systems (IS) and operations management (OM).

This study looks beyond firm boundaries to depict supply chain (SC) adaptability and classifies it into internal, customer and supplier dimensions to investigate their performance implications, respectively. This study also examines the enablers of SC adaptability based on information processing theory.

This study applies the structural equation modeling method to investigate relationships among SC information sharing, SC adaptability and operational performance using data collected from 216 manufacturers in China.

Internal information sharing has a positive impact on three dimensions of SC adaptability, whereas supplier and customer information sharing only have a positive impact on supplier adaptability. Customer and supplier information sharing interact to positively influence the three dimensions of SC adaptability, while internal and customer information sharing interact to negatively affect customer adaptability. We also find that all the three dimensions of SC adaptability can enhance operational performance.

This study contributes to providing a holistic definition of SC adaptability and classifies it into three dimensions. It also investigates antecedents and performance outcomes of SC adaptability.

An agile supply chain (SC) is critical in achieving competitive advantages in the vulnerable environment. Based on the competence–capability–performance paradigm, this study aims to investigate how information technology (IT) usage and employee multi-skilling influence internal, supplier and customer agility that are the three dimensions of SC agility. It further explores relationships between SC agility dimensions and SC performance.

This study used a survey method to collect primary data and sampled 216 Chinese manufacturing firms in different industries. Construct validity and reliability were confirmed. Structural equation modeling was used to test hypotheses.

The findings indicate that internal agility is the baseline of SC agility, which improves supplier and customer agility. IT usage is more important than employee multi-skilling in facilitating SC agility. The former improves all three dimensions, whereas the latter only improves internal agility. Both internal and supplier agility can improve SC performance, whereas customer agility has no significant effect.

This study contributes to the SC agility literature in two folds. On the one hand, based on the dynamic capability perspective, this research clarifies three dimensions of SC agility and their interrelationships. On the other hand, integrating competence–capability–performance paradigm with information processing view, this research investigates the antecedent and outcome of SC agility. In addition, to date, this is one of the first studies to simultaneously examine the effect of two critical competencies, namely, IT usage and employee multi-skilling on SC agility.

Despite the importance, no study exists which investigates the role of human resource (HR) in supply chain (SC) learning. This study aims to investigate the effects of high-performance human resource management (HRM) practices on different types of the SC learning (i.e. supplier, customer and internal learning) and innovation performance.

This study applies structural equation modeling to test the conceptual model based on data collected from 213 manufacturing firms in China.

The findings indicate that empowerment improves all three dimensions of SC learning, whereas training improves supplier and internal learning and teamwork is not related to any dimension of SC learning. These HRM practices also interactively influence SC learning dimensions. Moreover, customer and internal learning are directly related to innovation performance, while supplier leaning has a complementary effect with internal leaning but a substitutional effect with customer learning to innovation performance.

This study only selects training, teamwork and empowerment to manifest high-performance HRM practices. The impacts of high-performance HRM practices on different dimensions of SC learning and innovation performance are tested empirically with cross sectional-data collected only from manufacturing firms in China.

The findings suggest that managers can promote SC learning through the empowerment and training of their employees. Moreover, managers should place more emphasis on customer and internal learning to improve innovation performance.

Combining HRM and supply chain management (SCM) fields, this study offers a new framework to understand linkages between high-performance HRM practices, SC learning and innovation performance by using an empirical method.

Despite the recognition that supply chain (SC) learning is important for competitive advantage, little is known how to enable such learning. The purpose of this paper is to examine the effects of information technology (IT) application on different types of SC learning (i.e. internal, customer and supplier learning) and service performance.

This study applies structural equation modeling to test the conceptual model based on data collected from 213 manufacturing firms in China.

Although strategic application has a direct and negative relationship with all three dimensions of SC learning, it indirectly and positively improves SC learning through tactical and operational application. The authors observe that tactical application is positively related to all three dimensions of SC learning, while operational application improves internal and customer learning only. The authors also notice that internal and customer learning are positively related to service performance.

This study classifies IT application into strategic, tactical and operational dimensions, which may not adequately cover the entire set of IT application portfolio.

The findings suggest managers to use corresponding IT application to improve SC learning and service performance.

This study provides a new framework to understand the relationships between IT application, SC learning and service performance.

Underpinned by the lens of Contingency Theory (CT), the purpose of this paper is to empirically evaluate whether the impact of social media analytics (SMA) on customer satisfaction (CS) is contingent on the characteristics of different external stakeholders, including business partners (i.e. partner diversity), competitors (i.e. localised competition) and customers (i.e. customer engagement).

Using both subjective and objective measures from multiple sources, we collected primary data from 141 hotels operating in Greece and their archival data from TripAdvisor and the Hellenic Chamber of Hotels (HCH) database to test the hypothesised relationships. Data were analysed through structural equation modelling.

This study confirms the positive association between SMA and CS, but it remains subject to the varied characteristics of external stakeholders. We find that an increase in CS due to the implementation of SMA is more pronounced for firms that (1) adopt a selective distribution strategy where a limited number of business partners are chosen for collaboration or (2) operate in a highly competitive local environment. The results further indicate that high level of customer engagement amplifies the moderating effect of partner diversity (when it is low) and localised competition (when it is high) on the SMA–CS relationship.

The study provides novel insights for managers on the need to consider external stakeholder characteristics when implementing SMA to enhance firms' CS, and for researchers on the value of studying SMA implementation from the CT perspective.

E-commerce poverty alleviation (EPA) is an innovative poverty alleviation model in China. The institutional mechanisms of the e-commerce platform improve the effect of EPA and exert online shopping purchase power in rural China. From a socio-technical perspective, this paper used adoption readiness of farmers and perceived risk to construct an integrated model to discern the effect of enhanced e-commerce institutional mechanisms on farmers' online shopping intention in the context of EPA.

The survey included 832 valid samples from rural farmers in Shanxi province. This study analyses using structural equation modelling (SEM) and bootstrap methods used to empirically test the model.

Findings suggest that enhanced e-commerce institutional mechanisms have significant direct and indirect positive impacts on farmers' online shopping intention; adoption readiness and perceived risk play partial mediation roles in determining the relationship between farmers' online shopping intention and enhanced e-commerce institutional mechanisms; and the indirect mediation effect of adoption readiness is greater than that of perceived risk.

Although the proposed model was supported in the questionnaire survey, the investigation method was not completely excluded. Future research can combine the method of panel data and apply the framework to other e-commerce platforms, as well as to other cultural settings.

The study suggests that enhanced e-commerce institutional mechanisms that are based on the needs of farmers from poverty-stricken areas change the shopping habits of farmers. Moreover, enhanced e-commerce institutional mechanisms should allow farmers' perceived adoption readiness to play its promoting role and reduce the impeding role of perceived risk. The results of this study are conducive to the intensive implementation of the ‘Three Rural Issues’ strategy in China.

A new model to generate a two-factor mediation effect model by integrating the perceived effectiveness of enhanced e-commerce institutional mechanisms with farmers, farmers' adoption readiness, perceived risk and online shopping intention. The study explored the relationship between enhanced e-commerce institutional mechanisms and farmers' online shopping intention, bridging the gap in related empirical studies. Besides, this study first proposed farmers' adoption readiness and clarifies the mediating role of farmers' adoption readiness and perceived risk, which highlights the previously unnoticed role of farmers' adoption readiness.

Social media has become an important part of daily interpersonal communication in contemporary society. The purpose of this paper is to explore the attitudes of UK consumers by identifying the hidden information in tweets, and provide a framework which can assist industry practitioners in managing social media data.

Using a large-scale dataset of tweets relating to the Horsemeat scandal of 2013, a comprehensive data analysis framework, which comprises multidimensional scaling and sentiment analysis, alongside other methods, was applied to explore customers’ opinions.

Making jokes in social media was a main trend in the tweets relating to Tesco during the Horsemeat scandal. Consumer sentiments were overall negative and burgers were the most mentioned product in the week-long period after the story broke. The posting of tweets was correlated with the timing of news coverage, which indicates that the traditional media is still crucial to public opinion formation.

This paper presents a progressive tweet-mining framework that can serve as a tool for academia and practitioners in crisis management. The proposed framework indicates the significant importance of timely categorising the topics, identifying the sentiment of tweets and understanding the changes of consumer opinions over time in a crisis.

The research presented in this paper is one of the limited social media research to focus on a UK food fraud issue and adds to the limited body of literature investigating consumer social media use from the side of industry practitioners.