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The purpose of this paper is to examine how knowledge inflows and outflows interact to affect performance outcomes. Though previous studies have dealt with knowledge inflows and outflows, the quality and quantity characteristics of knowledge are often not taken into account, thus leaving a research gap with regards to the effect of their interactions on performance outcomes.

Based on Poisson regression analysis, this quantitative study fills the aforementioned research gaps by analyzing the ambidextrous configurations of knowledge flows from an ambidexterity perspective and examines their effects on two-phase performance (i.e. regular season and playoffs), using a longitudinal data set of National Basketball Association transactions from the 2003-2004 to 2014-2015 season.

The results suggest that the complementarity between knowledge inflows and outflows along the quality and quantity dimensions of knowledge, respectively, has a positive impact on two-phase performance, while the imbalance between knowledge inflows and outflows under the quality and quantity dimensions of knowledge, respectively, has a negative impact on playoffs performance (Phase 2). These findings suggest that organizations can balance knowledge inflows and outflows under a single quality or quantity dimension of knowledge. Furthermore, the interaction between the quantity of the inflows of knowledge and the quality of the outflows of knowledge and the interaction between the quality of the inflows of knowledge and the quantity of the outflows of knowledge are both positively related to two-phase performance. These findings suggest that organizations can balance knowledge inflows and outflows across quality and quantity dimensions of knowledge. Finally, the effects of the interaction between knowledge inflows and outflows on playoffs performance are greater than regular-season.

Organizations should leverage ambidexterity to manage/balance knowledge inflows and outflows across quality and quantity dimensions, further enhancing performance outcomes.

This study, first, provides new insights into knowledge flows by distinguishing between the quality and quantity of knowledge, the inflows and outflows of knowledge, constructing ambidextrous configurations of knowledge flows from an ambidexterity perspective. Second, it contributes to the relationship between knowledge flows and organizational performance by revealing how ambidextrous configurations of knowledge flows exert different effects on performance outcomes. Third, it adds to the literature of ambidexterity-performance relationships and expands it to the context of sports.

This study aims to examine the effects of formal and informal institutional factors (i.e. marketization and guanxi culture) on interorganizational conflicts (IOCs) and their interaction effects.

Drawing on IOC literature and an institution-based view, the authors use a sample of 12,022 Chinese firms from the World Bank’s Investment Climate Survey. A zero-inflated negative binomial regression was used to analyze the data.

The results suggest that guanxi culture has U-shaped effects, but marketization does not negatively affect IOCs. Furthermore, a low level of marketization weakens the U-shaped effect of guanxi culture on IOCs. A moderate level of guanxi culture can enable marketization to reduce IOCs.

This study provides a better understanding of the management of IOCs. Managers should fully understand the differential effects of the institutional environment in different regions and their interactions by adopting different response strategies.

This study enriches the literature on IOCs’ antecedents and contextual factors by examining the institutions’ direct and interaction effects on IOCs.

This study attempts to examine the performance differences between firms with and without integrated management systems (IMSs), and the impact of three integration strategies (i.e. implementing quality management system (QMS) first, then environmental management system (EMS) (QMS + EMS); implementing EMS first, then QMS (EMS + QMS); implementing QMS and EMS simultaneously (QMS − EMS)) on firm performance to reveal the IMS–performance relationship and provide empirical evidence.

Two panel datasets were collected during 2009–2019. This study used the Mann–Whitney non-parametric test and a sample of 33,155 observations from 4,316 Chinese listed firms to compare the performance differences between the IMS and non-IMS groups through performance indicators. This study also examined the effects of three integration strategies on firm performance using a cross-sectional time-series feasible generalized least squares (FGLS) regression model and a sample of 11,289 observations from 2,037 firms.

The results show that significant performance differences exist between IMS and non-IMS firms; however, the performance of firms with an IMS is not always better than that of firms without IMS. Furthermore, the simultaneous integration strategy has a positive impact, whereas sequential integration strategies (QMS + EMS and EMS + QMS) negatively affect firm performance. Compared with the EMS + QMS strategies, the QMS + EMS strategies have a more prominent effect on firm performance. Simultaneous strategies are more effective than sequential strategies.

Firms should fully consider the potential benefits and costs associated with the difficulties of IMS implementation and the implementation order of different management systems and the potential effects of the management systems in different conditions. Firms also should try to develop internal capabilities through implementing different integration strategies.

By comparing performance differences between firms with and without IMS, this study enriches the understanding of the performance benefits of IMS implementation in the Chinese context. By examining the impact of integration strategies that follow different sequences on firm performance, this study promotes an in-depth understanding of the integration strategies and their performance implications beyond simple descriptions and also provides new insights into operations strategy models.

This study aims to obtain diamond-coated mechanical seals with improved sealing performance and considerable cost. To achieve this purpose, the study focuses on depositing uniform, wear-resistant and easily polished diamond coatings on massive mechanical seals in a large-scale vacuum chamber.

The computational fluid dynamics simulation test and its corresponding deposition experiment are carried out to improve the uniformity of diamond films on massive mechanical seals. The polishing properties and sealing performance of mechanical seals coated with three different diamond films (microcrystalline diamond [MCD], nanocrystalline diamond [NCD] and microcrystalline/nanocrystalline diamond [MNCD]) and uncoated mechanical seals are comparatively studied using the polishing tests and dynamic seal tests to obtain the optimized diamond coating type on the mechanical seals.

The substrate rotation and four gas outlets distribution are helpful for depositing uniform diamond coatings on massive mechanical seals. The MNCD-coated mechanical seal shows the advantages of high polishing efficiency in the initial polishing process and excellent wear resistance and self-lubrication property in the follow-up polishing period because of its unique composite diamond film structures. The MNCD-coated mechanical seal shows the longest working life under dry friction condition, about 14, 1.27 and 1.9 times of that for the uncoated, MCD and NCD coated mechanical seals, respectively.

The effect of substrate rotation and gas outlets distribution on temperature and gas flow field during diamond deposition procedure is simulated. The MNCD-coated mechanical seal exhibits a superior sealing performance compared with the MCD-coated, NCD-coated and uncoated mechanical seals, which is helpful for decreasing the operating system shut-down frequency and saving operating energy consumption.

Traffic flow prediction has always been a top priority of intelligent transportation systems. There are many mature methods for short-term traffic flow prediction. However, the existing methods are often insufficient in capturing long-term spatial-temporal dependencies. To predict long-term dependencies more accurately, in this paper, a new and more effective traffic flow prediction model is proposed.

This paper proposes a new and more effective traffic flow prediction model, named channel attention-based spatial-temporal graph neural networks. A graph convolutional network is used to extract local spatial-temporal correlations, a channel attention mechanism is used to enhance the influence of nearby spatial-temporal dependencies on decision-making and a transformer mechanism is used to capture long-term dependencies.

The proposed model is applied to two common highway datasets: METR-LA collected in Los Angeles and PEMS-BAY collected in the California Bay Area. This model outperforms the other five in terms of performance on three performance metrics a popular model.

(1) Based on the spatial-temporal synchronization graph convolution module, a spatial-temporal channel attention module is designed to increase the influence of proximity dependence on decision-making by enhancing or suppressing different channels. (2) To better capture long-term dependencies, the transformer module is introduced.

The paper aims to investigate tool wear mechanism and tool geometry optimization of drilling PCB fixture hole.

An experimental study was carried out to investigate the chip formation and tool wear mechanism of drilling PCB fixture holes. Two types of drill with different types of chip-split groove were used in this study. The performances of these two types of drill bots were evaluated by tool wear and the shapes of chips.

The chips of drilling fixture holes contain aluminum chips from the cover board, copper chips from the copper foil, discontinuous glass fiber and resin from the CFRP. Feed rate and drilling speed have a great influence on the chip morphology. Abrasive wear of the drill lip is the main reason of the fixture drill bit in drilling PCB, and micro-chipping is observed on the tool nose and chisel edge. The influence of distance between the chip-split groove and drill point center on the axial force and torque is not obvious.

In this paper, hole wall roughness and drilling temperature were not analyzed in the optimization of drilling parameters. The future research work should consider them.

This paper investigated the mechanism of burr formation and tool wear in drilling of PCB fixture holes. Tool geometry was optimized by adding chip-split grooves.