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The purpose of this paper is to contextually theorise the different patterns of emerging multinational companies’ (EMNCs’) learning processes for innovation and the different influences of their technology-driven FDIs (TFDIs) on the processes.

A comparative case study method and process tracing technique are employed to investigate how and why firms’ learning processes for innovation took place, how and why the TFDIs emerged and influenced the firms’ learning processes in different ways.

The paper identifies two different patterns of learning process for innovation (Glider model vs Helicopter model) and two different roles of the case firms’ TFDIs (accelerator vs starter) in the different contexts of their learning processes. It is found that the capability building of the domestic wind energy industry has an important influence on the case of EMNCs’ learning processes and thus on the roles of their TFDIs.

The limitation of the paper lies in its small number of cases in a specific industry of a specific country. The two contextually identified learning models and roles of TFDIs may not be applied to other industries or other countries. Future research should investigate more cases in broader sectoral and geographic scope to test the models and also to identify new models.

For EMNCs, who wants to use the Helicopter model to rapidly gain production and innovation capability, cross-cultural management and integration management are crucial to practitioners. For emerging countries with ambitions to explore the global knowledge and technology pool, besides of the EMNC’s capability building, the capability building in the domestic industries should not be overlooked by policy makers.

The paper develops a dynamic and contextual analytical framework which helps to answer the important questions about how and under what context a TFDI emerges and influences firm’s learning process for innovation. It theorises the EMNCs’ learning process and TFDIs in the context of the development of the domestic industry. It strengthens the explanatory power of the learning-based view and adds new knowledge to the current FSA/CSA discourse in the international business literature.

China is a critical factor for constructing an all-round well-off society. Infrastructure construction, especially high-grade highways, in the western area is an essential component of the strategy for large-scale development of west China. It is crucial to evaluate investment projects for high-grade highways and select the best one. Testing investment projects and selecting the best one can be recognized as a multicriteria decision-making (MCDM) problem. In this process, decision-makers (DMs) usually face with uncertain information because of complicated decision environment or their limited knowledge.

A new Evaluation based on the Distance from Average Solution (EDAS) for PFS based on the DEMATEL is proposed: The authors offer a new score function and prove some properties for the score function. They put forward a novel Decision-making Trial and Evaluation Laboratory (DEMATEL) method for PFS to analyze the relations of criteria and get criteria weights. Considering the bounded rationality of DM, the authors propose a new EDAS method for PFS based on prospect theory. They apply their proposed approach to a western city's actual case in selecting a suitable project for building a high-grade highway.

By comparison, the authors can observe that our method has some traits: (1) considering bounded rationality of DM; (2) fewer computation; (3) having the ability to obtain the relation of criteria and finding the critical factor in the decision system.

In this paper, the authors propose a new EDAS method for PFS based on the DEMATEL technique. They transform PFS into crisp numbers by their proposed new score function for PFN to make the decision process more convenient. Then, the authors use the DEMATEL method to obtain the relationship between criteria and criteria weights. Furthermore, they propose a new EDAS method for PFS based on DEMATEL to reduce the computational complexity. Finally, they apply our method to a real case and compare our method with two traditional methods.

This study aims to research the development trend, research status, research results and existing problems of the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge.

Based on the investigation and analysis of the development history, structure form, structural parameters, stress characteristics, shear connector stress state, force transmission mechanism, and fatigue performance, aiming at the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge, the development trend, research status, research results and existing problems are expounded.

The shear-compression composite joint has become the main form in practice, featuring shortened length and simplified structure. The length of composite joints between 1.5 and 3.0 m has no significant effect on the stress and force transmission laws of the main girder. The reasonable thickness of the bearing plate is 40–70 mm. The calculation theory and simplified calculation formula of the overall bearing capacity, the nonuniformity and distribution laws of the shear connector, the force transferring ratio of steel and concrete components, the fatigue failure mechanism and structural parameters effects are the focus of the research study.

This study puts forward some suggestions and prospects for the structural design and theoretical research of the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge.

This paper aims to enable the robot to obtain human-like compliant manipulation skills for the peg-in-hole (PiH) assembly task by learning from demonstration.

A modified dynamic movement primitives (DMPs) model with a novel hybrid force/position feedback in Cartesian space for the robotic PiH problem is proposed by learning from demonstration. To ensure a compliant interaction during the PiH insertion process, a Cartesian impedance control approach is used to track the trajectory generated by the modified DMPs.

The modified DMPs allow the robot to imitate the trajectory of demonstration efficiently and to generate a smoother trajectory. By taking advantage of force feedback, the robot shows compliant behavior and could adjust its pose actively to avoid a jam. This feedback mechanism significantly improves the dynamic performance of the interactive process. Both the simulation and the PiH experimental results show the feasibility and effectiveness of the proposed model.

The trajectory and the compliant manipulation skill of the human operator can be learned simultaneously by the new model. This method adopted a modified DMPs model in Cartesian space to generate a trajectory with a lower speed at the beginning of the motion, which can reduce the magnitude of the contact force.

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

This research investigates whether focal firms employ strategic supply chain information disclosure, focusing on the concealment of supplier and customer identities, as part of their supply chain environmental risk management strategies (supplier sustainability risk and customer loss risk, respectively).

Using a panel dataset of Chinese listed firms from 2009 to 2019 and utilizing the suppliers’ environmental punishment of peer firms (peer events) as an exogenous shock and employing ordinary least squares (OLS) estimation, this study conducts a regression analysis to test how focal firms disclose the identities of their suppliers and customers.

Our results indicate that focal firms prefer to hide the identities of their suppliers and customers following the environmental punishment of peer firms’ suppliers. In addition, supplier concentration weakens the effect of withholding supplier identities, whereas customer concentration strengthens the effect of hiding customer identities. Mechanism analysis shows that firms hide supplier identities to avoid their reputation being affected and hide customer identities to prevent the deterioration of customers’ reputations and thus impact their market share.

Our study reveals that reputation spillover is another crucial factor in supply chain transparency. It is also pioneering in applying the anonymity theory to explain focal firms’ information disclosure strategy in supply chains.

This study examines the effect of design quality (i.e. appearance, navigation, information and interactivity) on cognitive and affective involvement leading to continued intention to use the online learning application.

We assume that design quality potentially contributes to enhance the individual's involvement and excitement. An experimental prototype is developed for collecting data used to verify and validate the proposed research model and hypotheses. A partial-least-squares approach is used to analyze the data collected from the participants (n = 662).

Communication, aesthetic and information quality revealed to be strong determinants of both cognitive and affective involvement. However, font quality and user control positively influence cognitive involvement, while navigation quality and responsiveness were observed as significant indicators of affective involvement. Lastly, cognitive and affective involvement equally contribute to determining the continued intention to use.

This study will draw the attention of designers and practitioners towards the perception of users for providing appropriate and engaging learning resources.

Prevalent research in the online context is focused primarily on cognitive and utilization behavior. However, these works overlook the implication of design quality on cognitive and affective involvement.

The purpose of this paper is to better depict the features of individual and group behaviors in sequential decisions under the effect of public belief drift.

In this paper, the authors design a two‐shots game which is closer to decisions condition in the real market by using the method of experimental economics two shots game.

The experimental results show that information cascade occurs more frequently in the second stage and the decision accuracy is decreased. The conclusion may provide experimental evidence for the “Animal Spirits Theory” of Keynes. Additionally, decision‐maker ranking in the middle of the decision sequence systematically deviates from his/her private information in balance state.

As existing information cascade theory of one shot decision fails to describe the belief‐dependent mechanism, the authors design the multi‐shots information cascade experiment; in which every individual decision maker has more than one sequential decision chance on the same event.

This study aims to use the novel approach of applying the behavioural reasoning theory (BRT) to understand the relative influence of reason for and reason against the adoption of mobile learning applications (M-learning apps) among information technology (IT) and information technology enabled services (ITeS) employees.

This study surveys 680 employees of IT and ITeS companies in India to examine the adoption of M-learning apps for learning using the BRT and the primary data analysis was done using the partial least squares-structural equation modelling technique.

It is found that the context-specific adoption factors for M-learning apps are hedonic motivation, self-efficacy, learning autonomy, ubiquitous and relative advantage, whereas the reasons against adoption of the M-learning apps are traditional barrier, usage barrier and image barrier. It is also found that values of openness to change positively affect the reasons for adoption and do not significantly affect reasons against adoption of M-learning. Values of openness to change affect the attitude towards M-learning apps and attitude affects the adoption intention of M-learning apps for learning.

This cross-sectional study was conducted only in the Indian IT/ITeS firms and future research can be conducted in other sectors and countries to generalize the results.

This research uniquely highlights the adoption factors both for and against, which should be considered while developing marketing strategies for M-learning apps’ adoption. It is imperative for training managers to consider these factors during the selection of M-learning apps and for designers while designing the M-learning apps.

This study provides new insights towards the use of mobile apps for learning with the employees’ perspective using the BRT theory and it highlights the reason for adoption and reason against adoption of M-learning apps.