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The purpose of this study is to examine the strategies used by consumers to control themselves in the Singles’ Day promotion. It also examines how promotion and social influence affect consumers’ purchase behavior and post-purchase evaluation.

A mixed methods approach including a quantitative study (N = 480) and a follow-up qualitative study (N = 35) was conducted to verify the hypotheses and provide deeper insights.

This study demonstrates that consumers allocate in-store slack in shopping budgets to restrict unplanned purchases and in-store slack is positively related to post-purchase evaluation. Social influence, which helps consumers rationalize purchase decisions, has positive effects on planned purchases and post-purchase evaluation. Both promotion strength and promotion range moderate the relationship between in-store slack and unplanned purchases.

Most studies investigate how promotion designs affect consumers’ in-store decision-making. This study focuses on the Singles’ Day promotion in China and examines the tactics consumers use to control purchase behavior in the promotion.

Employee voice is crucial for organizations to identify problems and make timely adjustments. However, promoting voice in organizations is challenging. This study aims to investigate how social media use (SMU) in the workplace affects employee voice by examining its intrinsic mechanisms and boundary conditions. Specifically, this study examines the mediating roles of social identifications and the moderating effects of job-social media fit on the relationship between SMU and social identifications.

This study conducted a survey of 348 employees in China.

First, SMU affects voice through social identifications. Second, distinct identifications have different effects on voice, such that organizational identification positively affects employee voice, while relational identification positively affects promotive voice and negatively affects prohibitive voice. Third, when social media is highly suitable for the job, the positive effect of work-related SMU on organizational identification is strengthened, while the positive effect of social-related SMU on organizational identification is weakened.

The results indicate that different identifications have distinct impacts on voice. Additionally, this study reveals a double-edged sword effect of SMU on voice through different social identifications. Further, job-social media fit moderates the relationship between SMU and social identifications. These findings have important implications for organizations adopting social media.

The purpose of the paper is to examine the coevolutionary dynamics between multistage overseas mergers and acquisitions (M&A) integration and knowledge network reconfiguration and the impact of this coevolution on industrial technology innovation.

This paper builds a coevolution analysis framework in stages and constructs structural equation models for empirical tests using the Chinese technology-sourcing overseas M&A events that occurred from 2001 to 2012.

Overseas M&A integration and knowledge network reconfiguration are in a coevolutionary relationship, driving industrial technology innovation. The acquirer adopts initial integration degree that matches the resource relatedness between the acquiring and acquired parties, promoting initial industrial technology innovation through initial knowledge network reconfiguration. Initial knowledge network reconfiguration will feed back to the M&A integration decision in the mid-to-late stage through increasing knowledge similarity and narrowing network position difference. The higher the improvement of mid-to-late integration degree, the more it can drive mid-to-late industrial technology innovation through mid-to-late knowledge network reconfiguration.

Future research can accurately classify overseas M&A integration stages through case tracking and explore other network attributes.

Practical guidelines are provided for managers on how to implement a multistage overseas M&A integration strategy, optimize knowledge network reconfiguration and promote industrial technology innovation. Significant practical implications are presented, especially in academia, society and quality of life.

Different from the previous research considering M&A integration as a single-stage decision, this paper emphasizes the dynamics of the M&A integration process and explores the coevolution mechanism of multistage overseas M&A integration and knowledge network reconfiguration.

This paper aims to investigate whether executive compensation and internal control can prevent overseas compliance risks through the mediating influence of multinational corporation (MNC) legitimacy and the moderating role of institutional distance.

Based on a law and economics perspective and the “bad apple,” the “red barrel” and the “bad cellar” theory of business misconduct, this paper constructs a systematic framework of “compliance motivation MNC legitimacy overseas compliance risk prevention” from the individual, organizational and systematic levels and uses data of Chinese MNCs for empirical analysis.

Empirical data from Chinese MNCs show that overseas compliance risks are comprehensively affected by the factors of the individual, organizational and systematic levels. Higher executive compensation and internal control will reduce MNCs’ overseas compliance risks through MNC legitimacy acquisition; institutional distance hinders the positive effect of internal control on MNC legitimacy and therefore aggravates overseas compliance risks.

This paper contributes to the understanding of the overseas law-abiding and offence behavior of MNCs from a law and economics perspective and offers valuable insights on how to prevent the ever-increasing overseas compliance risks.

Although the literature has analyzed the factors of compliance behavior, they are not interrelated, let alone integrated in a systematic risk prevention framework. This paper applies a law and economic analysis framework to the study of the overseas compliance risks for the first time.

Post-merger integration (PMI) is driven by coevolving processes. This paper examines the coevolution of dynamic integration strategy and network reconstruction and explores how these processes systematically enable emerging market acquirers to upgrade innovation capabilities.

This paper conducts a multi-case study based on four Chinese overseas acquisitions of manufacturing firms. The data were collected from interviews and archival documentation.

This study develops a coevolutionary framework of dynamic integration strategy and network reconstruction to explain processes and mechanisms of an acquirer’s innovation capability upgrading. This framework identifies three network motivations, namely, network access, network connection and network synergy. Under different network motivations, dynamic transitions of the acquirer’s integration strategy coevolve with multi-level reconstruction of its networks. Collectively, they are important mechanisms driving innovation capability moves from imitation innovation to asportation and reimitation innovation and then to independent innovation.

This paper responds to a recent call for more insights into the dynamics of PMI and contributes to the research on emerging market multinational corporations’ post-acquisition integration. By integrating the M&A and networks literature, the paper provides evidence of unexplored mechanism of network changes during PMI. It reveals that how acquirers manage the dynamics of PMI to gradually achieve multi-level reconstruction of their networks. Based on a coevolutionary framework, the paper provides a process perspective on how the coevolution of PMI and network reconstruction promotes the upgrading of innovation capabilities.

The aim of this study is to understand thermal effects and surface topography of roller bearings with misaligned load under combination of multifactors by an experimental method.

A series of orthogonal experiments would need to be planned and performed. A ranking of impact degree of factors on edge effect and eccentric load effect can be learned with multivariate analysis of variance by Statistical Product and Service Solutions software. Influence rules of each individual factor can also be obtained through more experiments. A roller surface phase diagram both before and after test can be observed with metallographic microscope. An axial profile data of roller can be measured by PGI 3D Profiler, then a roller generatrix contour can be achieved through filtering measured signal with empirical mode decomposition method.

Slip fraction has most impact on edge effect, whereas tilting angle plays a key role in eccentric load effect. For the case of low temperature, skidding damage does not occur. Inversely, because of the high pressure in partial elastohydrodynamic lubrication caused by roller tilt, running-in occurs and micro asperity flattening is observed on a rough surface. And, the larger the tilting angle, the more obvious the micro-flattening and the greater the reduction of roller surface roughness after the test.

A lot of theoretical studies on thermal effect of roller bearings surface morphology have been published. However, there are little on relevant experimental study, especially on thermal effect with an integration of sliding, tilting and unbalance loading.

Post-merger integration (PMI) is driven by coevolving processes. By integrating the literature on acquisitions with that of knowledge networks, this paper highlights different reconstruction mechanisms for dual knowledge networks during PMI – namely, internal knowledge network coupling and external knowledge network embeddedness. This paper aims to examine their coevolutionary relationships with PMI.

A coevolutionary framework is tested using a latent growth model and cross-lagged models. The analysis is based on longitudinal data collected from 116 Chinese technology-sourcing overseas merger and acquisition firms.

This paper unearths a novel idea that variations in post-merger reconstruction of dual knowledge networks can explain why some acquirers increase the degree of integration faster than the others. The results show that the internal knowledge network coupling leads to more knowledge similarity and, in turn, causes a higher degree of integration. The external knowledge network embeddedness also causes higher relative network status of the acquirer, which consequently leads to a higher degree of integration. Furthermore, results from cross-lagged models confirm that an increase in the degree of integration positively influences subsequent changes in the internal knowledge network coupling and external knowledge network embeddedness, thus forming a coevolutionary relationship over time.

This paper responds to recent calls for more insights into the dynamics of PMI. By highlighting different reconstruction mechanisms for internal and external knowledge networks during PMI, this paper explains why it is important to understand PMI dynamics from a dual knowledge network perspective. This paper is the first to adopt a coevolutionary perspective and provide a more comprehensive dynamic framework between PMI and reconstruction of dual knowledge networks. Besides, this paper contributes to the research on emerging market multinational corporations’ cross-border merger and acquisition integration from a dynamic perspective, revealing the time effects of traditionally favored light-touch integration.

In high-speed processing, the influence on the machining accuracy of a machine tool is greatly caused by the thermal deformation of the motorized spindle; a further study on the thermal characteristics of the spindle is given in this paper. This study aims to reduce the thermal error and improve the performance of the machine tool by discussing the relationships between the temperature distributions and rotating accuracy caused by the thermal deformations of the spindle.

The paper opted for a method combining the theoretical analysis and the experimental study to study the thermal stability of the high-speed motorized spindle. First of all, a finite element model of the spindle was built with ANSYS, whereby temperature distributions and the thermal deformations were successively obtained at different speeds. And then, both the temperature field and the rotating accuracy of the motorized spindle were measured simultaneously by the thermal stability experiment. Finally, the experimental and theoretical results were compared and validated.

The thermal stability of the motorized spindle was studied in this paper, and some findings from the study were as follows: the spindle’s rotating accuracy maintained good in X direction but bad in Y and Z directions in terms of the deformations; the higher front-end temperature of the spindle which can significantly affect the rotating accuracy is needed to be controlled mainly; the recovery speed of the spindle deformation lagged behind the temperature’s fallback speed; the vibration graph about radial rotating sensitivity synthesized by X1 and X2 presented a trifoliate shape.

Based on a built test-bed which can synchronously measure the motorized spindle’s temperature distribution and rotating accuracy with five-point method, the coupling effects of the thermal deformation and temperature are embodied, and not only the vibration graph but also the thermal tilt angles can be gained. Therefore, considering the influence of the thermal deformation on the heat generated by the bearings, the paper fulfilled a study by which it was obtained that the front-end temperature of the spindle, which was higher and could significantly affect the rotating accuracy, needed to be controlled mainly.

The paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.

The paper used the vector error correction model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.

The conclusion and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.

This paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.