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This article aims to establish a dynamic Energy Performance Contract (EPC) risk allocation model for commercial buildings based on the theory of Incomplete Contract. The purpose is to fill the policy vacuum and allow stakeholders to manage risks in energy conservation management by EPCs to better adapt to climate change in the building sector.

The article chooses a qualitative research approach to depict the whole risk allocation picture of EPC projects and establish a dynamic EPC risk allocation model for commercial buildings in China. It starts with a comprehensive literature review on risks of EPCs. By modifying the theory of Incomplete Contract and adopting the so-called bow-tie model, a theoretical EPC risk allocation model is developed and verified by interview results. By discussing its application in the commercial building sector in China, an operational EPC three-stage risk allocation model is developed.

This study points out the contract incompleteness of the risk allocation for EPC projects and offered an operational method to guide practice. The reasonable risk allocation between building owners and Energy Service Companies can realize their bilateral targets on commercial building energy-saving benefits, which makes EPC more attractive for energy conservation.

Existing research focused mainly on static risk allocation. Less research was directed to the phased and dynamic risk allocation. This study developed a theoretical three-stage EPC risk allocation model, which provided the theoretical support for dynamic EPC risk allocation of EPC projects. By addressing the contract incompleteness of the risk allocation, an operational method is developed. This is a new approach to allocate risks for EPC projects in a dynamic and staged way.

Because of the complexity of technological innovation and the dynamics of the technological environment, it is impossible for a single firm to have all knowledge needed for technological innovation, making it essential for firms to conduct cross-border knowledge search and integration. However, it is very difficult for firms to acquire and assimilate cross-border knowledge. The purpose of this paper is to explore how an open innovation platform (OIP) helps firms to effectively search and integrate cross-border knowledge, and to understand the key roles that OIP plays during the cross-border knowledge search and integration processes.

This paper takes the case analysis method, which provides a comprehensively understanding on the complex process of cross-border knowledge search and integration as well as the internal mechanism. Drawing on the research paradigm of Eisenhardt (1989), Bakker and Akkerman (2014), this paper analyzes and verifies the mechanism of OIP cross-border knowledge search and integration based on extensive interviews.

First, this paper analyzes the process of cross-border knowledge search and integration through Haier open partnership ecosystem (HOPE), which is theoretically divided into three stages, including motivation formation, cross-border knowledge search and integration. These three stages have been further decomposed into the following seven steps: demands discovery, problems definition, problems decomposition, resource search, resource evaluation, technology redevelopment and test. In addition, this study investigates the manifestation of interrelationships among these stages and steps, depicting the pathways through which HOPE facilitates the firm’s cross-border knowledge search and integration. The conclusions indicate that OIP timely discovers the consumer demands during the motivation formation stage, effectively decomposes problems and find related technology resources during the search stage and improves the efficacy of integration stage.

This study reveals the mechanism of OIP cross-border knowledge search and integration and draws some valuable conclusions, which contribute to the literature on cross-border knowledge search, enrich the research on problem-solving and also propose a new perspective to study the roles of OIP on innovation. However, there are still some limitations. First, this study is built on a single platform (HOPE), further studies may focus on more platforms to ensure the conclusions of this paper. Second, this study conducts data analysis using a simple encoding analysis, so it is possible that some critical information is emitted while collating and analyzing data. Meanwhile, for the research methods, qualitative and quantitative methods can be combined to analyze related issues, then the correlation and corresponding mechanism can be incorporated into the same framework to further verify the conclusions and generalize the results.

This paper theoretically analyzes how and why HOPE helps firms search and integrate cross-border knowledge. It provides not only a reference for OIP but also a proven and effective way for companies’ acquiring and integrating cross-border knowledge. Then it will further improve firms’ innovative abilities, especially disruptive innovation abilities.

Technological innovation, especially disruptive innovation is not only a driving force of firms’ sustainable development but also a vital driver of national development. This paper clarified that OIP can help firms conduct successful disruptive innovation through cross-border knowledge search and integration, which will further increase national innovative competence and improve social welfare.

This paper extends the literature on the process of cross-border knowledge search and integration, as well as the roles of OIP. From a managerial standpoint, the conclusions have practical implications for firms to successfully acquire and integrate cross-border knowledge.

Gear transmissions are widely utilized in practice. This paper aims to uncouple the crack feature from the cracked time-varying mesh stiffness (TVMS) and investigate the effects of the crack on the nonlinear dynamics of a spur gear pair.

An approximate method to simulate the cracked TVMS is proposed by using an amplitude modulation function. The ratio of mesh stiffness loss is introduced to estimate the TVMS with different crack depths and angles. The dynamic responses are obtained by solving a torsional model which takes the non-loaded static transmission error, the backlash and the cracked TVMS into account. By using the bifurcation diagram, the largest Lyapunov exponent (LLE) and dynamic mesh force, the influences of crack on nonlinear behaviors are examined. The dynamic characteristics are identified from the phase diagram, Poincaré map, dynamic mesh force, time series and FFT spectra.

The comparison between the healthy and cracked gear pairs indicates that the crack affects the system motions, such as the obvious changes of impact force and unpredictable instability. Besides, the additive and difference combination frequencies can be found in periodic-1 and -2 motions, but they are covered in periodic-3 and chaotic motions. Deeper crack is an important determinant of the nonlinear behaviors at a higher speed.

The research provides an interesting perspective on cracked TVMS and reveals the connection between crack and nonlinear behaviors of the gear pairs.

Based on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on consumers' purchase intention.

The authors conducted two empirical experiments on a total of 508 subjects.

There is an interactive effect between social crowding and CSR statement type on consumers' purchase intention. Specifically, in high social crowding situations, concrete CSR statements lead to consumers' higher purchase intention, while in low social crowding situations, abstract CSR statements lead to consumers' higher purchase intention. Self-construal and processing fluency play a moderating and mediating role in the mechanism.

This research study contributes to the theoretical understanding of the interaction between social crowding and CSR statements, enriching the field of consumer behavior research on social crowding. Additionally, it offers practical insights for enterprises on how to present CSR information in crowded situations.

This study aims to investigate the mechanism of knowledge management within multinationals during the post COVID-19 era, with particular consideration given to the relationship between the cultural intelligence of top managers and knowledge-oriented leadership using fear of COVID-19 as a moderating factor.

Derived from upper echelons’ theory and research on knowledge management success (KMS), a theoretical model and associated hypotheses have been developed and tested. Structural equation modeling was used with statistics collected from 288 top managers and executives of multinational corporations dominated by knowledge-intensive industries through a network investigation.

Results indicate that the levels of executives’ cultural intelligence and knowledge-oriented leadership contribute to KMS, while knowledge-oriented leadership acts as a mediator between them. In addition, the fear of COVID-19 of senior executives negatively affects both the direct and mediated influence of cultural intelligence on KMS.

The current research uses an empirical approach to examine cross-border KMS. Further research is needed to develop more comprehensive measurement tools for KMS and more detailed research by further developing the subdimensions of cultural intelligence. In addition, this paper used cross-sectional research that limits the capability to establish causal relationships over time.

The research explores the “human side” of the key antecedents of KMS, fills the gap in research about the impact of cultural intelligence and knowledge-oriented leadership on the achievement of KMS, paves the way for emerging knowledge-oriented leadership from the initial phase to the mature phase and contributes to the literature on environmental uncertainty and crisis, using the COVID-19 as a representative context.

This study highlights the effect of an inductee's altruism on referral reward programs (RRPs) on an online shopping guide platform to determine the optimal RRP and referral reward allocation under a Cashback and Referral RRP.

The authors consider a Stackelberg game with a platform, seller, inductor and inductee, where the inductee's altruism plays a vital role in determining the optimal RRP in equilibrium.

The authors show that the conditions under which it is optimal to reward the inductor only or reward both inductor and inductee are equal or unequal depending on the degree of the inductee's altruism. Suppose the platform is unable to dynamically decide the commission fee. In that case, the platform may not always be involved in RRPs and will gradually reduce the rewards for inductees as the altruism increases.

This study focuses on a free-to-consumers model where sellers pay membership fees. Thus, this study has limitations regarding other pricing schemes such as a model in which consumers pay a fee while sellers do not or a model in which both types of users pay fees.

This analytical work can help platforms optimize referral reward strategies and referral reward allocation considering the influence of an inductee's altruism.

In a Cashback and Referral RRP on a shopping guide platform, the authors provide applicable conditions for the platform to involve in the RRPs when rewarding an equal bonus for the inductor and inductee first. Further, the authors show the optimal referral reward strategy and referral reward allocation when giving the different bonuses to the inductor and inductee.