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Supply chain resilience (SCR) has attracted much attention in the context of the high uncertainty caused by the coronavirus disease 2019 (COVID-19), local regional conflicts and natural disasters. Based on information processing theory (IPT), this study investigates the role of supply chain information processing capability in enhancing SCR through supply chain governance (SCG), under different conditions of environmental uncertainty.

The hypothetical model is tested by using hierarchical regression on the primary samples collected from the Chinese manufacturing industry.

The results indicate that supply chain information processing capability has a significant positive effect on SCR. Also, SCG plays a mediating role between supply chain information processing capability and SCR. Furthermore, environmental uncertainty positively moderates the effect of supply chain information acquisition and supply chain information analysis on relational governance. However, environmental uncertainty only positively moderates the effect of supply chain information analysis on contractual governance.

This is the first study to explain the effect of information processing capability on SCR from the supply chain perspective, while also exploring the mediating role of SCG between SCR and supply chain information processing capacity, based on IPT.

The objective of this paper is to study the role of artificial intelligence (AI) in supporting the supplier scouting process, considering the information and the capabilities required to do so.

Twelve cases of IT and information providers offering AI-based scouting solutions were studied. The unit of analysis was the AI-based scouting solution, specifically the relationship between the provider and the buyer. Information processing theory (IPT) was adopted to address information processing needs (IPNs) and capabilities (IPCs).

Among buyers, IPNs in supplier scouting are high. IT and information providers can meet the needs of buyers through IPCs enabled by AI-based solutions. In this way, the fit between needs and capabilities can be reached.

The investigation of the role of AI in supplier scouting is original. The application of IPT to study the impact of AI in business processes is also novel. This paper contributes by investigating a phenomenon that is still unexplored and unconsolidated in a business context.

This study aims to investigate the impact of cross-functional coordination (cross-functional system, process and team coordination) on customer coordination (customer strategic and operational coordination) and operational performance. Following the lens of information processing theory (IPT), this study examines the diverse mechanisms of cross-functional coordination practices in enhancing firms’ information processing capabilities (IPCs) to cope with the higher information processing demands resulting from customer coordination, finally improving operational performance.

Based on data collected from 410 Chinese manufacturers, the authors use the structural equation modeling method to test the theoretical model.

The authors found that cross-functional system coordination is positively associated with customer operational coordination (COC) but not customer strategic coordination (CSC). Cross-functional process coordination increases both customer strategic and operational coordination. Cross-functional team coordination significantly promotes CSC but not COC. Both customer operational and strategic coordination facilitate operational performance.

This research pioneers in identifying three dimensions of cross-functional coordination based on IPT and examine their distinct impacts on various customer coordination activities. The authors distinguish two customer coordination dimensions and reveal their effects on operational performance. This research contributes to the development of IPT. Additionally, this study provides guidelines for managers to coordinate internal departments and collaborate with external customers to enhance firms’ operational performance.

Firms are increasingly pressured to comply with mandatory supply chain transparency (SCT) regulations. Drawing on information processing theory (IPT), this study aims to show how blockchain technology can address information uncertainty and equivocality in assuring regulatory compliance in an interorganizational network (ION).

IPT is applied in a single case study of an ION in the mining industry that aimed to implement blockchain to address mandatory SCT regulations. The authors build on a rich proprietary data set consisting of interviews and substantial secondary material from actors along the supply chain.

The case shows that blockchain creates equality between actors, enables compliance and enhances efficiency in an ION, reducing information uncertainty and equivocality arising from conflict minerals regulation. The system promotes engagement and data sharing between parties while protecting commercial sensitive information. The lack of central authority prevents larger partners from taking control. The system provides mineral provenance and a regulation-compliant record. System cost analysis shows that the system is efficient as it is inexpensive relative to volumes and values of metals transacted. Issues were identified related to collecting richer human rights data for assurance and compliance with due diligence regulations.

The authors provide some of the first evidence in the operations and supply chain management literature of the specific architecture, costs and limitations of using blockchain for SCT. Using an IPT lens in an ION setting, the authors demonstrate how blockchain-based systems can address two key IPT challenges: environmental uncertainty and equivocality.

The purpose of this study is to explore how demolition contractors coordinate project activities for buildings at their end-of-life. The organizations are thereby conceptualized as information processing systems facing uncertainty.

A multiple-case study methodology was selected to gain in-depth insights from three projects with different end-of-life strategies: a faculty building (material recycling), a nursing home (component reuse) and a psychiatric hospital (element reuse). Using a theory elaboration approach, the authors sought to explain how and why demolition contractors process information for end-of-life coordination.

End-of-life strategies differ in the degree of building, workflow and environmental uncertainty posed to the demolition contractor. Whether or not a strategy is effective depends on the (mis)match between the specific levels of uncertainty and the adopted coordination mechanisms.

The explanatory account on end-of-life coordination refines information processing theory for the context of (selective) demolition projects.

The detailed case descriptions and information processing perspective enable practitioners to select, implement and reflect on coordination mechanisms for demolition/deconstruction projects at hand.

Reflecting its dual conceptual-empirical and inductive-deductive focus, this study contributes with new opportunities to explain building end-of-life coordination with a refined theory.

The purpose of this paper is to explore the effects that customer structured and unstructured information sharing (IS) can have on customer operational and strategic coordination and on supply chain performance (SCP). In addition, the study examines how customer IS influences customer coordination under various levels of demand uncertainty (DU).

The conceptual model for this study is designed on the basis of information-processing theory (IPT). Using data collected from 622 manufacturers in mainland China and Taiwan, the theoretical model is tested using the structural equation modeling method.

The authors find that both customer structured IS and unstructured IS are positively associated with customer strategic coordination. Customer structured IS increases customer operational coordination, but customer unstructured IS does not. DU positively moderates the relations between customer unstructured IS and strategic coordination, and between customer structured IS and operational coordination. Also, DU negatively moderates the relationship between customer structured IS and strategic coordination. Customer strategic coordination is positively related to SCP and to operational coordination. Customer operational coordination has no significant impact on SCP.

This study deepens our understanding of customer IS by distinguishing between customer structured and unstructured IS. The study also provides a greater understanding of customer coordination by making a distinction between the customer strategic and the operational coordination. The findings extend the empirical application of IPT. In addition, this study’s findings direct SC managers to apply varied customer IS practices that can enhance specific kinds of customer coordination activities, thereby enabling improved SCP.

The purpose of this paper is to investigate the implications for supply chain risk management (SCRM) by applying internet of things (IoT). Therefore, the impact and effects on the SCRM process, as well as the internal and external pathway and the outcome of SCRM are examined.

This study adopts a multiple case study methodology with twelve companies from the manufacturing industry. This study is guided by the information processing theory (IPT) and a theory-grounded research framework to provide insights into information requirements and information processing capabilities for IoT-supported SCRM.

The studied cases demonstrate an increase in data availability in the companies that contribute to improved process transparency and process management. Furthermore, the process steps, risk transparency, risk knowledge and risk strategies have been enhanced, which enabled improved SCRM performance by fitting information requirements and information processing capabilities, thus allowing for competitive advantage.

This study offers in-depth insights for SCRM managers into the structure of IoT systems, primary use cases and changes for the process itself. Furthermore, implications for employees, incentives and barriers are identified, which could be used to redesign SCRM.

This study addresses the requirement for additional empirical research on technology-enhanced SCRM, supported by IPT as a theoretical foundation. The radical change of SCRM by IoT is demonstrated while discussing the human role, implications for SCRM strategies and identifying relevant topics for future development.

Inter-organisational governance is an important enabler for information processing, particularly in relationships undergoing digital transformation (DT) where partners depend on each other for information in decision-making. Based on information processing theory (IPT), the authors theoretically and empirically investigate how governance mechanisms address information asymmetry (uncertainty and equivocality) arising in capturing, sharing and interpreting information generated by digital technologies.

IPT is applied to four cases of public–private relationships in the Dutch infrastructure sector that aim to enhance the quantity and quality of information-based decision-making by implementing digital technologies. The investigated relationships are characterised by differing degrees and types of information uncertainty and equivocality. The authors build on rich data sets including archival data, observations, contract documents and interviews.

Addressing information uncertainty requires invoking contractual control and coordination. Contract clauses should be precise and incentive schemes functional in terms of information requirements. Information equivocality is best addressed by using relational governance. Identifying information requirements and reducing information uncertainty are a prerequisite for the transformation activities that organisations perform to reduce information equivocality.

The study offers insights into the roles of both governance mechanisms in managing information asymmetry in public–private relationships. The study uncovers key activities for gathering, sharing and transforming information when using digital technologies.

This study draws on IPT to study public–private relationships undergoing DT. The study links contractual control and coordination as well as relational governance mechanisms to information-processing activities that organisations deploy to reduce information uncertainty and equivocality.

The purpose of this study is to develop a synthesized conceptual framework for artificial intelligence (AI) adoption in the field of business-to-business (B2B) marketing.

A conceptual development approach has been adopted, based on a content analysis of 59 papers in peer-reviewed academic journals, to identify drivers, barriers, practices and consequences of AI adoption in B2B marketing. Based on these analyses and findings, a conceptual model is developed.

This paper identifies the following two key drivers of AI adoption: the shortcomings of current marketing activities and the external pressure imposed by informatization. Seven outcomes are identified, namely, efficiency improvements, accuracy improvements, better decision-making, customer relationship improvements, sales increases, cost reductions and risk reductions. Based on information processing theory and organizational learning theory (OLT), an integrated conceptual framework is developed to explain the relationship between each construct of AI adoption in B2B marketing.

This study is the first conceptual paper that synthesizes drivers, barriers and outcomes of AI adoption in B2B marketing. The conceptual model derived from the combination of information processing theory and OLT provides a comprehensive framework for future work and opens avenues of research on this topic. This paper contributes to both AI literature and B2B literature.

Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances.

This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences.

SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL.

Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes.

This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL.