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The purpose of this paper is to propose a novel prospect-based two-sided matching decision model for matching supply and demand of technological knowledge assisted by a broker. This model enables the analyst to account for the stakeholders’ psychological behaviours and their impact on the matching decision in an open innovation setting.

The prospect theory and grey relational analysis are used to develop the proposed two-sided matching decision framework.

By properly calibrating model parameters, the case study demonstrates that the proposed approach can be applied to real-world technological knowledge trading in a market for technology (MFT) and yields matching results that are more consistent with the reality.

The proposed model does not differentiate the types of knowledge exchanged (established vs novel, tacit vs codified, general vs specialized) (Ardito et al., 2016, Nielsen and Nielsen, 2009). Moreover, the model focuses on incorporating psychological behaviour of the MFT participants and does not consider their other characteristics.

The proposed model can be applied to achieve a better matching between technological knowledge suppliers and users in a broker-assisted MFT.

A better matching between technological knowledge suppliers and users can enhance the success of open innovation, thereby contributing to the betterment of the society.

This paper furnishes a novel theoretical model for matching supply and demand in a broker-assisted MFT. Methodologically, the proposed model can effectively capture market participants’ psychological considerations.

This paper mainly focuses on how to induce all members to represent members' true preferences for supply and demand matching of E-commerce platform in order to generate stable matching schemes with more social welfare of Multi-agent Matching Platform (MMP) and individually stable advantages than traditional methods.

An MMP is designed. Meanwhile, a true preference inducing method, Lower-Bid Ranking (LBR), is proposed to reduce the number of false preferences, which is helpful to solve the problem that too much false preferences leads to low efficiency of platform operation and supply and demand matching. Then, a systematic model of LBR-based Stable Matching (SM-LBR) is proposed.

To obtain an ideal transaction partner, the adequate preference ordering and modifying according to market environment is needed for everyone, and the platform should give full play to the platforms' information advantages and process historical transaction and cooperation data. Meanwhile, the appropriate supply and demand matching is beneficial to improve the efficiency and quality of platform operation, and the design of matching guidance mechanism is essential.

The numerical experiments show that, the proposed model (SM-LBR) can induce members to represent the model's true preferences for stable matching and generate effective matchings with more social welfare of MMP and individually stable advantages than traditional methods, which may provide necessary method and model reference for the research of stable matching and E-commerce platform operation.

Risks can easily disrupt the demand–supply match targeted by sales and operations planning (S&OP). As surprisingly little is known of how organizations identify, assess, treat and monitor risks through tactical planning processes, this paper zooms in on the S&OP set-up and process parameters to explore how risks are managed through S&OP.

A multiple case study analyzes the S&OP processes of seven organizations in the process industry, drawing on 17 in-depth interviews with high-ranking representatives, internal and external documents, and a group meeting with participating organizations.

The study finds that organizations proactively design their S&OP based on their main risk focus stemming from the planning environment. In turn, such designs proactively support organizations' risk identification, assessment, treatment and monitoring through their S&OP execution. Reactively, a crisis S&OP meeting – making use of the structure of S&OP – can be used as a risk-treatment tool, and S&OP design can be temporarily adapted to deal with emerging risks.

This study is among the first to empirically elucidate risk management through S&OP. S&OP design, execution and adaption are identified as three interconnected strategies that allow organizations to manage risks. The design enables risk management activities in the monthly execution of S&OP. The reactive role of S&OP in risk management is particularly novel.

The purpose of this paper is to explore the effects of demand planning practices on the disruptions induced by operational risk. The study reveals whether the negative consequences of operational risk factors (covering demand, supply, control and process risks) can be absorbed or amplified through the application of specific demand planning practices in supply chains.

The study involves the partial least squares path model procedure. Likewise, the items of the constructs in the outer model were subjected to a purification process by principal component analysis with the orthogonal (varimax) and oblique (Promax) methods of rotation.

The findings suggest that although one may not observe uniformity and standardization in the role of demand planning in alleviating the negative effects of operational risks, still some regularities can be obtained. Having said that some demand planning practices tend to mitigate or reinforce disruptions driven by operational risk, whereas the other practices simultaneously absorb and amplify disruptions driven by operational risk.

The study shows that different managerial instruments, which are not inherently dedicated to risk management, when appropriately applied, may have an indirect impact on the mitigation of supply chain risk. In particular, the concept of demand planning might be very helpful for managers when dealing with demand and control risks.

The study simultaneously examines a more detailed bundle of practices forming the demand planning process. The research attempts to investigate the link between the demand planning process and operational risk consequences, derived from all sources (supply, demand, process and control). The paper shows that risk management is not a sole tool to mitigate disruptions. Among the concepts, which contribute to decrease risks is the demand planning process. The study demonstrates that the demand planning process when applied as a component of supply chain management, may contribute to mitigate certain operational risks.

Outlines the main findings of a study of a process in a major organization (involved in the servicing of capital equipment) which seeks to predict customer demand for service calls and match these against engineering resources. The process is called the engineer availability process (EAP) and has been examined in two geographical areas of the host company. Among the findings is that, no matter what means are used to predict demand, there is always a need for a flexible revision of supply. This revision can be met between formal and informal clustering of engineers. The former delivers a consistent output of jobs per day across a clustered team whereas with informal clustering, the distribution across teams is less consistent and puts greater pressure on individual teams to match supply and demand.

The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry.

The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises.

NLSPD is directly related to the degree of supply–demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM.

The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM.

NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap.

The purpose of this paper is to find out the current SCM skill development priorities in manufacturing firms and how the structural properties of the supply chain translate into demand for SCM skills in manufacturing firms.

An internet survey was designed and conducted. The responses of 154 manufacturing companies operating in Finland were analysed through descriptive statistics and regression analyses.

The supply chain management skills with an inter‐organisational focus tend to have a higher development priority than the skills with an intra‐organisational focus. The top five skills for development are: demand forecasting and supply planning; sourcing and supplier management; customer and distribution channel management; production planning and control; and information systems for logistics and production planning. Structural properties of the supply chain seem to have an effect on skills that are related to supply chain design and information flow infrastructure, i.e. the ability to locate the various nodes in the network, and to connect and coordinate their respective activities in the face of often uncertain demand.

The results are based on survey research with a limited sample size and geographic coverage with bias towards large firms. The research scope is further limited to investigating the influence of structural properties of the supply chain, leaving opportunities for further research on the demand for SCM skills.

The authors report original findings that provide input to the development processes of training programmes and university curricula, related to supply chain management. They also initiate theory development on the determinants of demand for SCM skills.

The peer-to-peer (P2P) accommodation-sharing market has developed rapidly on the strength of information technology in recent years. Matching providers and customers in an information technology (IT)-enabled platform is a key determinant of both parties' experiences and the healthy development of the platform. However, previous research has not sufficiently explained the mechanism of provider–customer matching in accommodation sharing, especially at the psychological level. Based on field cognitive style theory, this study examines how the match and mismatch affect customers' online and offline satisfaction and whether a significant difference exists between online and offline satisfaction under different matching patterns.

The authors test the proposed theoretical model using 122 provider–customer dyad data collected through a field study.

The results suggest that customers' online and offline satisfaction under match is significantly higher than that under mismatch. In addition, customers' online satisfaction is significantly higher than their offline satisfaction under mismatch, but there is no significant difference between the two under match. The perceived price fairness also plays a moderating role in the case of mismatch.

In summary, these findings provide a novel understanding about the matching patterns and their outcomes in the accommodation-sharing context and expand the contents and applications of field cognitive style theory and matching theory. This study will help these IT-enabled platforms to provide personalized matching services at the psychological level, thereby enhancing user experience and corporate competitiveness. 10; 10;

The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.

This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.

This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.

Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

Material conscious and information network (MCIN) is a kind of cyber physics social system. This paper aims to study the MCIN modeling method and design the MCIN-based architecture of smart agriculture (MCIN-ASA) which is different from current vertical architecture and involves production, management and commerce. Architecture is composed of three MCIN-ASA participants which are MCIN-ASA enterprises, individuals and commodity.

Architecture uses enterprises and individuals personalized portals as the carriers which are linked precisely with each other through a peer-to-peer network called six-degrees-of-separation block-chain. The authors want to establish a self-organization, open and ecological operational system which includes active, personalized consumption, direct, centralized distribution, distributed and smart production.

The paper models three main MCIN-ASA participants, namely, design the smart supply, demand and management functions, which show the feasibility innovation and high efficiency of implementing MCIN on agriculture. At the same time, the paper presents a prototype system based on the architecture.

The authors think that MCIN-ASA improves current agriculture greatly and inspires a lot in production-marketing-combined electronic commerce.