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This paper aims to present a technique for optimal trajectory planning of industrial robots that applies a new harmony search (HS) algorithm.

The new HS optimization algorithm adds one more operation to the original HS algorithm. The objective function to be minimized is the trajectory execution time subject to kinematical and mechanical constraints. The trajectory is built by quintic B‐spline curves and cubic B‐spline curves.

Simulation experiments have been undertaken using a 6‐DOF robot QH165. The results show that the proposed technique is valid and that the trajectory obtained using quintic B‐spline curves is smoother than the trajectory using cubic B‐spline curves.

The proposed new HS algorithm is more efficient than the sequential quadratic programming method (SQP) and the original HS method. The proposed technique is applicable to any industrial robot and yields smooth and time‐optimal trajectories.

This paper aims to propose a shape factor for granular materials based on particle shape. The scientific goal is to investigate the influence of particle shape on the mechanical properties of rockfill materials.

The method of generating four regular-shaped particles is based on the observation that most rockfill grains are regarded as like-triangle, like-rhombus, like-square and like-hexagon. A shape factor F that is developed using the Blaschke coefficient and a concave–convex degree is proposed. A biaxial compression test on rockfill materials under stress path is numerically simulated by discrete element method. The evolution of the shape factor F under the simulated stress paths is analyzed, and particle breakage rate, peak intensity and peak-related internal friction angle for rockfill materials are derived. A method of determining the shape factor F involved in the two functions is proposed.

A new micro-parameter is calibrated using the test data of one rockfill material. Particle shape greatly affects the particle breakage rate, peak intensity and peak-related internal friction angle for rockfill materials. The final experimental grading curves all approach the particle breakage grading curve proposed by Einav (the fractal dimension is 2.7).

This study proposes a shape factor F, which describes the geometric features of natural rockfill particles. The proposed shape factor F has a simple structure, and its parameters are easy to determine. The method provides an opportunity for a quantitative study on the particle shape of granular materials, and this study helps to better understand the influence of particle shape on the mechanical characteristics of rockfill materials.

This paper aims to examine whether and how gender diversity and CEO gender can influence firm value in the emerging market of Pakistan. The study further tests whether these relations vary across state-owned enterprises (SOE) and non-state-owned enterprises (NSOE).

This study considers Pakistani listed firms over the period 2010-2017. The firms have been divided into SOE and NSOE for additional analysis. Tobin’s Q is used to measure firm’s value.

The authors document that female directors (FDirectors) on corporate boards is positively associated with firm value. The findings also illustrate that female CEOs (FCEOs) enhances a firm value. Additional analyses show that the influence of FDirectors and FCEOs on firm value is stronger in NSOE than in SOE.

The results suggest that gender diversity and CEO gender play a significant role in corporate decisions. The findings imply that FDirectors discipline the management, reduce agency conflicts and thereby improve corporate governance, resulting in higher firm value.

This study has two important contributions. First, while prior studies mostly based their arguments on using gender diversity of corporate boards, this study shows that a firm performance can be significantly improved if a female serves as a CEO. Second, this study also tests the stated relations for SOE and NSOE and show that gender diversity plays a significant role in NSOE than in SOE.

This research intends to analyze the innovation ecosystem factors that play a vital role in firm performance. As a result, large-scale empirical studies on the innovation ecosystem are rare, and fewer efforts have been made to determine if and how different factors affect the ecosystem models of firms. There has yet to be a substantial empirical study on the innovation ecosystem.

Data were acquired from Pakistani IT companies. The results show that factors of the innovation ecosystem significantly contribute to business performance. The essential assumption is that resource endowment, organizational culture, knowledge and competence, and technology capability are allied to the innovation ecosystem.

The findings are crucial from a managerial view because firms must focus on changing their innovation ecosystem factors model to achieve greater performance. Radical changes in the firms will only be worthwhile if they value their resource endowments. To attain superior firm performance via influential factors of the innovation ecosystem, IT administrators need to build organizational cultural capacities to adapt to changes brought on by digitization quickly and effectively. However, this must be supplemented by improving organizational knowledge, competencies and technological capabilities to enable organizations to modify their ecosystems.

Eventually, firms can better respond to changes in their settings if they combine these variables by implementing an effective innovation ecosystem model, which leads to greater sector and superior financial performance.

The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type, there is currently no model that considers the time factor to accurately calculate the CFP of hospital building throughout their life cycle. This paper aims to establish a CFP calculation model that covers the life cycle of hospital building and considers time factor.

On the basis of field and literature research, the basic framework is built using dynamic life cycle assessment (DLCA), and the gray prediction model is used to predict the future value. Finally, a CFP model covering the whole life cycle has been constructed and applied to a hospital building in China.

The results applied to the case show that the CO₂ emission in the operation stage of the hospital building is much higher than that in other stages, and the total CO₂ emission in the dynamic and static analysis operation stage accounts for 83.66% and 79.03%, respectively; the difference of annual average emission of CO₂ reached 28.33%. The research results show that DLCA is more accurate than traditional static life cycle assessment (LCA) when measuring long-term objects such as carbon emissions in the whole life cycle of hospital building.

This research established a carbon emission calculation model that covers the life cycle of hospital building and considered time factor, which enriches the research on carbon emission of hospital building, a special and extensive public building, and dynamically quantifies the resource consumption of hospital building in the life cycle. This paper provided a certain reference for the green design, energy saving, emission reduction and efficient use of hospital building, obviously, the limitation is that this model is only applicable to hospital building.

The purpose of this paper is to review systematically the research of grey relation analysis (GRA) models.

Three different approaches, the springboard to build a GRA model, the angle of view in modelling, and the dimension of objects, are analysed, respectively.

The GRA models developed from the models based on relation coefficients of each point in the sequences in early days to the generalized GRA models based on integral or overall perspective. It evolved from the GRA models which measure similarity based on nearness, into the models which consider similarity and nearness, respectively. The objects of the research advanced from the analysis of relationship among curves to that among curved surfaces, and further to the analysis of relationship in three‐dimensional space and even the relationship among super surfaces in n‐dimensional space.

The further research on GRA models is proposed. One is about the property of GRA model. An in‐depth knowledge about the properties of GRA model will help people to understand its function, applicable area and requirements for modelling. The other one is about the extension of research object system. The object to be analysed should be extended from the common sequence of real numbers to grey numbers, vectors, matrices, and even multi‐dimensional matrices, etc.

This study examines the impact of ownership structure on firm financial performance, for 146 manufacturing firms listed at the Pakistan Stock Exchange (PSX) for the period 2003–2012.

The theoretical background of the present study is based on the agency theory. Ownership structure is measured by institutional shareholdings, insider shareholdings, foreign shareholders and government shareholdings, while return on assets (ROA), return on equity (ROE), market-to-book ratio (MBR) and Tobin's Q (TQ) are used as proxies of corporate financial performance. The dynamic panel generalized method of moments (GMM) method is employed to cater for the issue of endogeneity.

We find that institutional ownership exerts a significant positive impact on ROE and MBR, which suggests that institutional investors play a significant role in improving the financial performance of the sample Pakistani. Furthermore, the results reveal a significant positive relationship of insider ownership with ROA, ROE, MBR and TQ, which is consistent with the prediction of agency theory that concentration of insider ownership aligns the interest of shareholders with those of the managers and hence improves performance. A significant positive association of government shareholdings with ROA and ROE was also found. Therefore, policymakers may encourage government ownership in firms, which can help to improve corporate financial performance.

The present study contributes to the existing literature on ownership structure and corporate financial performance in an emerging market like Pakistan. It is worth mentioning that the institutional setup and corporate governance structure in Pakistan is yet at an evolving stage. Findings of this study may provide useful insights to corporate managers and investors about the relationship between ownership structure and financial performance of firms from the manufacturing sector in Pakistan.

The purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.

The definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.

The negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.

The proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.

The definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

This paper aims to make a call for the establishment of a new research journal: a likely title for which would be Chinese Public Management. The background to this is clearly set out here for posterity’s sake. The review of selected papers unveils an emerging trend amongst Chinese researchers for undertaking deeper, cluster-based analyses. See, for example, the insights presented in this issue concerning competitiveness in China’s automobile industry.

A diary-like account has been made of the series of recent events that sparked the author’s interest in creating a journal to be known as Chinese Public Management. Why is there currently this focus on empirical research for public policy? From the author’s five years’ work for a serial visiting professorship across China, he has found that there are now well-established, substantial databases dedicated to the subject. Even more importantly – as this paper illustrates – a growing community of scholars has become keen to embark upon an in-depth, quantitative research. Perhaps, for the new journal, we would need an editor concentrating specifically on databases. Furthermore, undertaking scholarly work that is still of practical relevance for guiding authorities in their formulations of public policy will add a whole new dimension to the available research.

There is scope for a new endeavor that documents management research within the public sector in China. This may be seen as a sister journal for “Chinese Management Studies” that focuses on the other, much larger Chinese sector, that is, governmental organizations.

This paper documents the emergence of the necessity for a new journal about management in China.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.