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Session-based recommendation aims to predict the user's next preference based on the user's recent activities. Although most existing studies consider the global characteristics of items, they only learn the global characteristics of items based on a single connection relationship, which cannot fully capture the complex transformation relationship between items. We believe that multiple relationships between items in learning sessions can improve the performance of session recommendation tasks and the scalability of recommendation models. At the same time, high-quality global features of the item help to explore the potential common preferences of users.

This work proposes a session-based recommendation method with a multi-relation global context–enhanced network to capture this global transition relationship. Specifically, we construct a multi-relation global item graph based on a group of sessions, use a graded attention mechanism to learn different types of connection relations independently and obtain the global feature of the item according to the multi-relation weight.

We did related experiments on three benchmark datasets. The experimental results show that our proposed model is superior to the existing state-of-the-art methods, which verifies the effectiveness of our model.

First, we construct a multi-relation global item graph to learn the complex transition relations of the global context of the item and effectively mine the potential association of items between different sessions. Second, our model effectively improves the scalability of the model by obtaining high-quality item global features and enables some previously unconsidered items to make it onto the candidate list.

The incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers’ responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.

Based on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of “network stage”, “consumer type”, and “resource type” to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.

The results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.

Under the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers > agent consumers > commenting consumers > potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.

This paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises’ customer relationship management and marketing decisions.

The cruise industry has witnessed steady growth, with passenger volume increasing from 17.8 million in 2009 to 30 million in 2019. In the context of global competition and an uncertain business environment, competition in business has changed dramatically from battles of “firm versus firm” to “supply chain versus supply chain”. Hence, the purpose of this paper is to understand the cruise industry from a chain perspective, which has not drawn widespread research attention.

This paper brings together the insights, opinions, concepts and frameworks from a literature review of different disciplines (maritime shipping, tourism management, logistics management, operations management and supply chain management) and analysis results from 22 semi-structured interviews to make an early attempt to conceptualise the cruise supply chain (CSC).

The cruise supply chain is elaborated on the process, the role of each entity and its characteristics by comparing with the maritime supply chain and tourism supply chain. Based on the understanding of the CSC, two specific characteristics of the Chinese CSC are examined, which need further investigation.

The CSC is articulated with detailed processes and characteristics based on the literature review and empirical study. The findings of this paper not only advance the knowledge of the supply chain in the cruise industry but also highlight the importance of further research on the CSC.

The purpose of this paper is the research of a novel gesture-based dual-robot collaborative interaction interface, which achieves the gesture recognition when both hands overlap. This paper designs a hybrid-sensor gesture recognition platform to detect the both-hand data for dual-robot control.

This paper uses a combination of Leap Motion and PrimeSense in the vertical direction, which detects both-hand data in real time. When there is occlusion between hands, each hand is detected by one of the sensors, and a quaternion-based algorithm is used to realize the conversion of two sensors corresponding to different coordinate systems. When there is no occlusion, the data are fused by a self-adaptive weight fusion algorithm. Then the collision detection algorithm is used to detect the collision between robots to ensure safety. Finally, the data are transmitted to the dual robots.

This interface is implemented on a dual-robot system consisting of two 6-DOF robots. The dual-robot cooperative experiment indicates that the proposed interface is feasible and effective, and it takes less time to operate and has higher interaction efficiency.

A novel gesture-based dual-robot collaborative interface is proposed. It overcomes the problem of gesture occlusion in two-hand interaction with low computational complexity and low equipment cost. The proposed interface can perform a long-term stable tracking of the two-hand gestures even if there is occlusion between the hands. Meanwhile, it reduces the number of hand reset to reduce the operation time. The proposed interface achieves a natural and safe interaction between the human and the dual robot.

The purpose of this paper is twofold: to identify, evaluate and structure the research that focusses on omni-channel retailing from the perspective of logistics and supply chain management; and to reveal the intellectual foundation of omni-channel retailing research.

The paper applies a multi-method approach by conducting a content-analysis-based literature review of 70 academic papers. Based on the reference lists of these papers, the authors performed a citation and co-citation analysis based on the 34 most frequently cited papers. This analysis included multidimensional scaling, a cluster analysis and factor analysis.

The study reveals the limited consideration of logistics and supply chain management literature in the foundation of the omni-channel retailing research. Further, the authors see a dominance of empirical research as compared to conceptual and analytical research. Overall, there is a focus on the Western retail context in this research field. The intellectual foundation is embedded in the marketing discipline and can be characterised as lacking a robust theoretical foundation.

The contribution of this research is identifying, evaluating and structuring the literature of omni-channel research and providing an overview of the state of the art of this research area considering its interdisciplinary nature. This paper thus supports researchers looking to holistically comprehend, prioritise and use the underpinning literature central to the phenomena of omni-channel retailing. For practitioners and academics alike, the findings can trigger and support future research and an evolving understanding of omni-channel retailing.

The purpose of this paper is to bridge together seemingly disparate yet interconnected paradigmatic antecedents of e-tailing and servicescape, i.e., product assortment, order fulfillment, shopping assistance and its consequences for shopping efficiency.

The proposed conceptual model is well grounded in the extensive literature from e-tailing as well as retailing domain and to assess the plausibility of the model. Total 246 female online apparel shoppers were surveyed from an Indian university and the data were analyzed using structural equation modeling through SmartPLS.

The outcomes of the study indicate that the e-customer may derive a substantial share of shopping assistance and service interface through product assortment offered by e-tailing sites. Customer-perceived performance of this e-shopping process – a crucial element of e-tail servicescape – directly affects the shopping assistance, along with order fulfillment capability of retail scope.

The study used a sample of graduate students at a north-west university in India, which limits the generalizability of the research to other consumer groups. The paper links a significant body of literature within a conceptually developed framework and identifies key research areas in the e-tailing realm.

By better understanding the role of product assortment as a value-added feature in online value co-creation process, the e-tail managers can leverage the proposed integrated capability to improve e-tailing performance and customer outcomes in the form of business.

With rapid advancements in internet-led communication, we are witnessing the dawn of a new era of e-tail innovations around us which is expected to change the way people experience shopping.

This research is an attempt to enrich the level of understanding about online shopping environment in light of relationships among virtual and physical facets of e-tail, i.e., product assortment, order fulfillment, shopping assistance and shopping efficiency. The authors investigate customer-perceived product assortment performance in e-tailing and its significances on shopping outcomes.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

This work aims to address source and dynamics of institutional change. It seeks to develop analytic tools by adaptation of Schumpeterian notion on entrepreneurship, Nelson's work on basic institutions and specific institutions, and Nonaka's middle‐up‐down framework of knowledge management in contrast to top‐down process. Pragmatically it attempts to understand how to improve policy capacity that challenges China seriously.

The work adopts a detailed case study method. A paired case is chosen with the criteria that they have widespread impact in China, and are representative of general and specific institutional change, respectively. Data came from mixed sources: field work and publications. Comparison of the paired cases identifies similarities and differences of different institutional change.

Similarities in the cases are in the important role of institutional entrepreneurs, crucial necessity of field experimentation, and regulatory and legislative means of knowledge processing. Differences are that centralized “top‐down” process of knowledge development, together with committed and centrally guided field experimentation, characterizes general institutional change. In contrast, coordinated and distributed “middle‐up‐down” process, together with autonomously emerged creation at the grassroots, characterizes specific institutional change.

This is a new research area. Many more empirical and theoretical works are needed.

As to how China should improve policy capacity, the study indicates: to focus policy learning on specific parts and facets of institutional settings; to change policy‐makers' role from omni‐competent controller to catalyst/promoter of institutional change; to assign an active role to middle levels and allow broader participation and diverse experimentations.

The author explores interesting details of institutional entrepreneurship and institutional changes based on the two case studies. This work fills the gap of how to analyze institutional change from the innovation/innovation systems perspective.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.