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This study examines whether, how and when socially responsible human resource management (SRHRM) practices increase employees' in-role and extra-role corporate social responsibility (CSR) performance.

This study uses data from 422 employees of 68 companies.

SRHRM improves employees' in-role CSR-specific performance via impression management motivation and enhance extra-role CSR-specific performance via prosocial motivation. Moral identity symbolization strengthens the relationship between SRHRM and impression management motivation, and moral identity internalization reinforces the relationship between SRHRM and prosocial motivation. The authors also propose mediated moderation models.

This study indicates that company can adopt SRHRM practices to improve employees' in-role and extra-role CSR-specific performance.

This study reveals how and when SRHRM practices influence employees' CSR-specific performance and sheds light on the social impacts of SRHRM.

Omnichannel retail are catching increasing attention from multiple research area, due to its widespread and essential application in retailing industry. The principal object of this paper is to systematically review current studies on omnichannel retail in information systems, operations and marketing research area. Further, the second purpose of this study is to provide insights and guides on omnichannel research to facilitate advance research in the area.

A systematic review on omnichannel retail in retailing industry has been conducted. 33 research articles from 2014 to 2020 from Financial Times 50 journals (FT 50 journals) were identified to be reviewed. The articles were reviewed on the basis of study area namely: information systems, operations and marketing. These research areas were further divided into subcategories to provide in-depth and crystal clear review of literature.

The review outcome showed that omnichannel topics are active in management studies. There are three main research areas: information systems, operations management and marketing. This study found that IT enhances channel capabilities and expands demand in omnichannel retail; operations can be better optimized based on understanding of cross-channel interactions, product category and retailer types; consumer heterogeneity, product category, channel capabilities and retailer type are all found to contribute to complexities of omnichannel marketing.

This study provides a pioneering review to gauge the updated literature concerned with omnichannel research in terms of IT, operations and marketing perspective. Further, a systematic literature review provides insights and guides for future significant studies on potential research subjects.

Simultaneous hydrofracturing of multiple perforation clusters in vertical wells has been applied in the stimulation of hydrocarbon resources reservoirs. This technology is significantly impeded due to the challenges in its application to the multilayered reservoirs that comprise multiple interlayers. One of the challenges is the accurate understanding and characterization of propagation and deflection of the multiple hydraulic fractures between reservoirs and embedded interlayers.

Numerical models of the tight multilayered reservoirs containing multiple interlayers were established to study hydrofracturing of multiple perforation clusters and its influencing factors on unstable propagation and deflection of hydraulic fractures. Brittle and plastic multilayered reservoirs fully considering the influences of different in situ stress ratio and physical attributes for reservoir and interlayer strata on propagations of hydraulic fractures were investigated. The combined finite element–discrete element method and mesh refinement strategy were adopted to guarantee the accuracy of stress solutions and reliability of fracture path in computation.

Results show that the shear stress fields between adjacent multiple hydraulic fractures are superposed to cause fractures deflection. Stress shadows induce the shielding effects of hydraulic fractures and inhibit fractures growth to emerge unstable propagation behaviors, and a main single fracture and several minor fractures develop. As the in situ stress ratio increases, hydraulic fractures more easily deflect toward the direction of maximum in situ stress, and stress shadow and mutual interaction effects between them are intensified. Compared to brittle reservoir, plastic-enhanced reservoir may limit fracture growth and cannot form long fracture length; nevertheless, plastic properties of reservoir are prone to induce more microseismic events with larger magnitude.

The obtained fracturing behaviors and mechanisms based on engineering-scale multilayered reservoir may provide effective schemes for controlling and estimating the unstable propagation of multiple hydraulic fractures.

The purpose of this paper is to investigate the effect of share pledging by controlling shareholders on earnings informativeness.

Using a sample of 23,120 firm-year observations from 2003 to 2019 in China, this paper examines how share pledging by controlling shareholders affects earnings informativeness, measured by earnings persistence and earnings response coefficients.

This paper finds that share pledging by controlling shareholders makes earnings less informative. The adverse impacts are more pronounced when share pledging distorts incentives of controlling shareholders to a greater extent and when the signaling of share pledging about a firm’s weak future performance is stronger. Finally, this paper further shows that the 2018 new regulation on share pledging effectively alleviates the negative impacts of share pledging on earnings informativeness.

First, this paper adds to the growing literature on the economic consequence of share pledging by documenting the adverse impacts of share pledging on earnings informativeness. The literature on the economic consequence of share pledging is often mixed, which justifies further research on the impacts of share pledging on earnings informativeness. Second, this paper documents a new signaling channel through which share pledging affects earnings informativeness. Third, the finding of this paper on the 2018 new regulation on share pledging may be interesting to research agencies, such as the Chartered Financial analyst institute and Institutional Shareholder Services institute that recommend tightening regulations on share pledging.

The purpose of this paper is to investigate the effect of long horizon institutional ownership on CEO career concerns to meet the short-term earnings benchmark.

Using a sample of 10,565 firm-year observations in the USA, the paper examines the extent to which long horizon institutional investors mitigate the positive relation between CEO turnover and missing the quarterly consensus analyst forecast.

After controlling for the general performance-turnover relation, this paper finds that long horizon institutional investors mitigate the positive relation between CEO turnover and missing the quarterly consensus analyst forecast. This finding is stronger when CEOs focus on long-term value creation and do not sacrifice long-term value to boost current earnings and is stronger when the monitoring intensity by long horizon institutional investors is greater.

The results suggest that long horizon institutional investors serve a monitoring role in alleviating CEO career concerns to meet the short-term earnings benchmark.

This paper contributes to the literature on the relation between long horizon institutional ownership and attenuated managerial short-termism. The literature is silent about why long horizon institutional investors alleviate managerial short-termism. This paper fills this void in the literature by documenting that long horizon institutional investors mitigate CEO career concerns for managerial short-termism. Moreover, this paper contributes to the literature on the monitoring role of institutional investors by documenting the incremental effect of institutional ownership on CEO career concerns to meet the short-term earnings benchmark.

The purpose of this study is to determine the tribological behavior and wear mechanism of a polytetrafluoroethylene (PTFE)/polyester (PET) fabric composite for application as a self-lubricating liner suitable for high-speed and low-load friction conditions.

The effects of different loads and sliding speeds on the friction coefficients and wear characteristics of the composite were studied using reciprocating friction tests. Scanning electron microscopy, extended depth-of-field microscopy, and energy-dispersive X-ray spectrometry was used to analyze the worn surface morphology, wear depth and elemental content of the lubrication films, respectively.

The friction coefficient curves of the composites presented a long-term steady wear stage under different sliding conditions. With increasing sliding speed, the friction coefficient and wear depth of the composite slowly increased. The film-forming mechanism of the composite revealed that the PTFE/PET ply yarn on the composite surface formed complete PTFE lubrication films at the initial sliding stage.

The PTFE/PET fabric composite maintained good friction stability and high-speed adaptability, which demonstrates that the composite has broad application prospects as a highly reliable self-lubricating bearing liner with a long lifespan.

It is widely accepted that business excellence comes from firm-specific factors. However, it is still unclear how institutional relatedness – the degree of embeddedness with the dominant institutions that confer resources and legitimacy, influences the business excellence of the firm. The purpose of this study is to explore the influence of three kinds of institutional relatedness, i.e. home government ties, initial public offerings (IPOs) and alliances with foreign firms, on the business excellence of Chinese firms.

This study uses a sample of firms enlisted on the “Most Respected Companies” rank in China during the period 2002–2015 and their paired firms who are absent from the list, by means of ordinary least square regression estimator, to explore the relationship between institutional relatedness and business excellence.

The empirical results suggest that IPOs and alliances with foreign firms significantly strengthen firms’ business excellence. Furthermore, home government ties have positive effects on outbound IPOs and alliances with foreign firms but hinder business excellence.

This study extends the business excellence literature by characterizing institutional rather than firm-specific factors from an institution-based view. It also enriches research on outcomes of institutional relatedness through investigating empirically its impact on business excellence. The findings provide new insights into the dual role of home government ties in achieving business excellence.

This paper aims to develop a novel algorithm and apply it to solve two-dimensional linear partial differential equations (PDEs). The proposed method is based on Chebyshev neural network and extreme learning machine (ELM) called Chebyshev extreme learning machine (Ch-ELM) method.

The network used in the proposed method is a single hidden layer feedforward neural network. The Kronecker product of two Chebyshev polynomials is used as basis function. The weights from the input layer to the hidden layer are fixed value 1. The weights from the hidden layer to the output layer can be obtained by using ELM algorithm to solve the linear equations established by PDEs and its definite conditions.

To verify the effectiveness of the proposed method, two-dimensional linear PDEs are selected and its numerical solutions are obtained by using the proposed method. The effectiveness of the proposed method is illustrated by comparing with the analytical solutions, and its superiority is illustrated by comparing with other existing algorithms.

Ch-ELM algorithm for solving two-dimensional linear PDEs is proposed. The algorithm has fast execution speed and high numerical accuracy.

The paper develops a decision-making model for supplier selection combining quality function deployment (QFD), analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The efficacy of the model was demonstrated by applying it for supplier selection of lithium ion batteries.

The proposed methodology involved identifying customer requirements for lithium ion batteries and translating them to requisite technical characteristics using QFD. Further, separate sourcing, safety and sustainability-related supplier parameters were proposed taking into account the manufacturer's point of view. The relative weight of each parameter was then calculated using AHP, and finally, TOPSIS was used to select the best supplier.

The proposed methodology was applied to six suppliers of lithium ion batteries, and the obtained results were used to select the most and least preferred suppliers.

The obtained results cannot be generalized and are valid to the case environment. However, the proposed approach can be used for any environment related to supplier selection after capturing the corresponding parameters. The proposed approach does not restrict the number of parameters to be considered.

Many researches related to supplier evaluation are reported in literature, but few studies are available related to supplier performance evaluation for lithium ion batteries using QFD, AHP and TOPSIS. The study will provide a guideline for comparing and selecting supplier on the basis of performance in general and its application to lithium ion batteries in specific.

The purpose of this paper is twofold: to incorporate the symbolic relationships among the attributes of customer requirements (CRs) and engineering characteristics (ECs) as well as to factor in the values numerically to enhance the prioritization process for an improved, comprehensive quality function deployment (QFD) analysis. The aim is to develop the concept of assimilating and factoring in the often-ignored interrelationships among CRs and ECs utilizing the weighted average method for the CR and EC correlations with overall calculations.

After a brief literature review of the methods utilized, the research paper discusses the framework for the correlation triangle challenge and introduces a novel mathematical solution utilizing triangle values in conjunction with computed initial raw weights for CRs and initial priority scores for ECs. The capability and applicability of the proposed model are demonstrated with a real-life example.

Through the proposed technique, the roof and the interrelationship triangle's signs and symbols are translated into numerical values for each permutation of ECs and CRs, and then the prioritization values are processed and finalized. The proposed model successfully modifies and removes vagueness from an otherwise overlooked part of the QFD process.

The illustrated case study aptly proves that the proposed methodology yields more revealing and informative outcomes for engineers and designers, thus adding much-needed reliability to the outcome and its analysis. The validation conducted through the rank comparison endorses the premise, and the results obtained reflect the strength and accuracy of the progressive QFD as a product planning tool.

The research article proposes a fresh and unique QFD approach that solves typical procedural complications encountered in a regular QFD. Whereas the traditional methods neglect the interrelationships among CRs and ECs, this new methodology employs them in an improved, numerical way by incorporating them in quantitative analysis, which leads to judicious and improved decision-making.