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Many firms struggle to implement strategies that can successfully enhance the environmental sustainability of their processes. Drawing on the theories of green intellectual capital and complementary assets, this study develops a model describing the mechanism whereby firms can translate a green (i.e., environmental) strategy into a superior green process innovation performance (GPIP).

Regression analysis of multi-source survey data collected from 514 managers at 257 firms (257 top management members and 257 safety or environmental managers) was used to test the hypotheses.

A firm's green strategic intent has positive effects on the three aspects of green intellectual capital (i.e., human, organizational and relational capital). In turn, these three aspects have positive effects on GPIP. Moreover, green organizational capital positively moderates the effect of green relational capital on GPIP, whereas it negatively moderates the effect of human capital on GPIP.

In order to implement a green strategy successfully, especially in polluted industries such as the chemical industry, managers need to develop not only the firm's tangible resources but also its intangible resources. The more they invest in green organizational capital, the higher the level of GPIP that can be achieved. On average, a firm's green human capital is more important than its organizational and relational capital. Moreover, its organizational capital helps capture the benefits of its relational capital, but it impairs the creativity of its human capital.

The authors contribute to the literature on green strategy implementation by suggesting that green intellectual capital plays a mediating role in the relationship between a firm's green strategic intent and GPIP.

Under the constraints of given passenger service level and coupling travel demand with train departure time, this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.

The authors optimize the train operational plan in a special network layout, i.e. an urban rail corridor with dead-end terminal yard, by decomposing it into two sub-problems: train timetable optimization and rolling stock circulation optimization. As for train timetable optimization, the authors propose a schedule-based passenger flow assignment method, construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm. For the optimization of rolling stock circulation, the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.

The case study shows that the train operational plan developed by the study's approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.

The example verifies the efficiency of the model and algorithm.

This paper aims to examine a two-way interaction between social influencers’ number of followers (micro vs meso) and argument quality (weak vs strong) on consumers’ self-reported and brain responses to advertising posts on Instagram. Further, drawing upon source credibility theory and contemporary theories of persuasion, the Instagram users’ perceptions of the influencer’s credibility are predicted to mediate the hypothesized effects.

Through an online (N = 192) and a lab study (N = 112), the authors examined Instagram users’ responses to an advertising post from Instagram influencers in terms of perceived source credibility and electronic word-of-mouth intention, using validated multi-item scales from existing literatures and electroencephalogram (EEG) measures. The hypotheses were tested with a 2 (type of influencer: micro vs meso) × 2 (argument quality: weak vs strong) between-subject design using mediated moderated linear regression analysis.

The results highlight that meso-influencers are perceived as a credible source of information only when their product-related post provides strong argument quality. Moreover, this process involves an increase in users’ cognitive work (measured with EEG), with possible implications on marketing communication strategies and online message design.

The limitations of the work can serve as ideas for future research. First, this study did not account for the influencer’s relevance and resonance. Second, the authors studied consumer responses to online communication produced by Instagram influencers within a single product category. Another important product type distinction that requires further attention is between hedonic and utilitarian products. Finally, the two studies only used positive review content. Further research should study how consumers evaluate the source credibility of a micro- vs meso-influencer when they are exposed to negative reviews containing weak vs strong arguments.

The results suggest that marketers should carefully consider Instagram influencers based on the trade-offs between credibility and reach. Specifically, micro-influencers are perceived as more credible sources of information than meso-influencers, which means that they have greater potential to affect Instagram users’ behavior. Moreover, the results suggest that meso-influencers should leverage argument quality to enhance their credibility and draw greater positive outcomes for the products and brands they endorse.

To the best of the authors’ knowledge, this study is the first to investigate how the interaction between the type of social media influencer and the argument quality affects consumers’ self-reported and brain responses to advertising posts on Instagram. Moreover, using neuroscience, this study aims to shed light on the neurophysiological processes that drive consumer responses to product-related communication posted by different influencer types.

How closely does the translation match the meaning of the reference has always been a key aspect of any machine translation (MT) service. Therefore, the primary goal of this research is to assess and compare translation adequacy in machine vs human translation (HT) from Arabic to English. The study looks into whether the MT product is adequate and more reliable than the HT. It also seeks to determine whether MT poses a real threat to professional Arabic–English translators.

Six different texts were chosen and translated from Arabic to English by two nonexpert undergraduate translation students as well as MT services, including Google Translate and Babylon Translation. The first system is free, whereas the second system is a fee-based service. Additionally, two expert translators developed a reference translation (RT) against which human and machine translations were compared and analyzed. Furthermore, the Sketch Engine software was utilized to examine the translations to determine if there is a significant difference between human and machine translations against the RT.

The findings indicated that when compared to the RT, there was no statistically significant difference between human and machine translations and that MTs were adequate translations. The human–machine relationship is mutually beneficial. However, MT will never be able to completely automated; rather, it will benefit rather than endanger humans. A translator who knows how to use MT will have an opportunity over those who are unfamiliar with the most up-to-date translation technology. As MTs improve, human translators may no longer be accurate translators, but rather editors and editing materials previously translated by machines.

The findings of this study provide valuable and practical implications for research in the field of MTs and for anyone interested in conducting MT research.

In general, this study is significant as it is a serious attempt at getting a better understanding of the efficiency of MT vs HT in translating the Arabic–English texts, and it will be beneficial for translators, students, educators as well as scholars in the field of translation.

Adopting the split complementizer phrase (CP) hypothesis, the paper aims at providing an account for object cliticization in Standard Arabic (SA) as an instance of object displacement. Kayne's proposal on cliticization is adopted here to account for the type of displacement in SA that objects clitics in SA, like full determiner phrases (DPs), obligatorily move from their base position as independent complements of the verb to the specifier of Foc first before attaching to the verb under the tense node.

This research adopts a qualitative interpretive research design (Creswell, 2007, 2010). The majority of the samples chosen for the study involve dependent pronominal objects obligatorily attached to the verb. The samples were judged to be grammatical based on the author's judgment as an native speaker of Arabic. Moreover, all the examples were checked for grammaticality by two full professors of Arabic grammar who are native speakers.

The analysis proposed that, like lexical DP's, pronominal objects originate as separate maximal projection (XP) constituents and move from their base position as verbal complements to the focus position [Spec, Foc]. In other words, both are able to move out of VP, targeting the same specifier position of a functional projection. This movement is focus-driven, that is, triggered by the edge feature on Foc. Pronominal objects at a later phase crucially higher than V0 (possibly in phonetic form (PF)) get cliticized to the verb which has adjoined to T.

Unlike displaced lexical DP objects in SA syntax, displaced pronominal objects, however, have received less critical attention especially within Rizzi's (1997, 2004) left periphery theory and, therefore, some areas of these constructions remain poorly understood.

The aim of this paper is to investigate the relationship between the ring structure of the twisted partial skew generalized power series ring RG,≤;Θ and the corresponding structure of its zero-divisor graph Γ̅RG,≤;Θ.

The authors first introduce the history and motivation of this paper. Secondly, the authors give a brief exposition of twisted partial skew generalized power series ring, in addition to presenting some properties of such structure, for instance, a-rigid ring, a-compatible ring and (G,a)-McCoy ring. Finally, the study’s main results are stated and proved.

The authors establish the relation between the diameter and girth of the zero-divisor graph of twisted partial skew generalized power series ring RG,≤;Θ and the zero-divisor graph of the ground ring R. The authors also provide counterexamples to demonstrate that some conditions of the results are not redundant. As well the authors indicate that some conditions of recent results can be omitted.

The results of the twisted partial skew generalized power series ring embrace a wide range of results of classical ring theoretic extensions, including Laurent (skew Laurent) polynomial ring, Laurent (skew Laurent) power series ring and group (skew group) ring and of course their partial skew versions.

The simulation of eddy currents in laminated iron cores by the finite element method (FEM) is of great interest in the design of electrical devices. Modeling each laminate by finite elements leads to extremely large nonlinear systems of equations impossible to solve with present computer resources reasonably. The purpose of this study is to show that the multiscale finite element method (MSFEM) overcomes this difficulty.

A new MSFEM approach for eddy currents of laminated nonlinear iron cores in three dimensions based on the magnetic vector potential is presented. How to construct the MSFEM approach in principal is shown. The MSFEM with the Biot–Savart field in the frequency domain, a higher-order approach, the time stepping method and with the harmonic balance method are introduced and studied.

Various simulations demonstrate the feasibility, efficiency and versatility of the new MSFEM.

The novel MSFEM solves true three-dimensional eddy current problems in laminated iron cores taking into account of the edge effect.

Higher education institutions are the contemporary embodiment of knowledge-intensive organizations. The role of knowledge sharing among academics in enhancing teaching, research and innovation performance cannot be overlooked. However, a paucity of studies were devoted to uncovering the influencing factors of knowledge sharing among academics in China. This study aims to dig into the factors that influence academics’ knowledge sharing behaviors in the context of Chinese higher education.

Semi-structured interviews were conducted with 13 academics from universities across various regions in China by using a combination of convenience, snowball and purposive sampling methods. Thematic analysis was employed where data sets were examined according to the initial categorization of factors based on a review of the literature while new factors were searched based on frequency of re-occurrence.

Perceived loss of power and time and effort significantly hinder knowledge sharing, whereas expected self-development and association are major catalysts of knowledge sharing. The organizational climate in higher education is featured by competition and individualism, which are not conducive to knowledge sharing, while affiliation and trust are essential for cultivating a pro-sharing environment. Technological tools are perceived as user-friendly and useful in facilitating knowledge sharing, but doubts were raised about the effectiveness of online knowledge sharing compared to face-to-face communication.

Deviating from the conventional quantitative approach, this study provides novelty insights on this topic by revealing some less-investigated factors of knowledge sharing among Chinese academics by taking the qualitative approach.

The purpose of this study is to explore the extent to which teamwork (developed either during an initial training phase or during a subsequent deployment phase) is influenced by the nature of the team’s environment (extreme vs non-extreme) and the extent to which teamwork is one of the explaining mechanisms for team performance.

Data was collected from 60 teams at 2 time-points: training phase in The Netherlands or Germany and deployment phase (in locations such as Afghanistan and Bosnia-Herzegovina).

This study’s results indicate that when teams consider working in extreme environments, they develop higher levels of teamwork as compared to teams expecting to work in non-extreme environments. These differences remain stable also during the deployment phase, such that teams operating in extreme environments will continue to have higher levels of teamwork as compared to teams operating in non-extreme environments.

With this study, the authors contribute to the teamwork quality research stream by empirically studying how teamwork quality develops in unique military contexts such as extreme environments. Studies in such contexts are relatively rare.