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The purpose of this paper is to examine the change in pension fund board diversity after self-regulation was introduced, and investigate which pension fund characteristics influence compliance with self-regulation. In addition, the authors analyze whether compliance might be achieved by tokenism.

The authors hand-collect pension fund and pension fund board data of the largest (by assets) 200 pension funds in the Netherlands. The authors compare descriptive statistics on board diversity, perform statistical tests on these, and perform non-linear regression techniques to investigate which pension fund characteristics influence compliance.

The findings are fourfold. First, over the past three years, pension fund boards have only marginally improved on gender and age diversity. In April 2014, still more than 35 percent of the funds had no women on the board, and an overwhelming 60 percent had no members below 40 years of age. This indicates that self-regulation in the pension fund industry so far has not been effective for the industry as a whole. Second, the authors find that pension funds that have larger boards are more likely to have at least one woman on the board or at least one member below 40 years of age. Third, boards of pension funds with more assets are less likely to have young board members. Fourth, boards with at least one female have a higher probability of also having at least one member below 40 years, which is suggestive of tokenism.

Based on Hirschman’s (1970) theory of voice and exit, the authors expect that pension fund boards would be more diverse than corporate boards. However, the authors find that this is not the case. Second, given the importance of generational value transfers in pension fund policy decisions, the authors expect that age is a more important diversity characteristic than gender for pension fund boards in the Netherlands. Again, the data does not support this prediction.

Consistent with the literature on diversity in corporate boards, the authors find that diverse boards are on average larger. This suggests that, all other things equal, small boards might want to reconsider whether increasing their size would lead to more diversity and hence to more voice for participants that cannot exit the pension scheme. If larger funds hesitate to include young members because of their lack of relevant skills, then the authors would recommend setting up a platform to educate young candidates and prepare them for board membership. Forced independent auditor verification, as in the UK, might be a fruitful action the regulator could enforce on pension funds going forward. However, if that also does not lead to a significant improvement, compulsory diversity quota might be the only option left for policy makers.

This paper contributes to the literature in at least three ways. First, the authors analyze whether self-regulation on diversity in pension fund boards has been effective. Second, the authors determine which pension fund characteristics are associated with more board diversity. Third, the authors shed light on tokenism in pension fund board composition: Diversity might be obtained through installing diversity tokens, which are individuals who have multiple diversity characteristics.

The purpose of this paper is to develop comprehensive criteria for evaluating fashion design schemes and used an integrated model which considers the interrelation between the clusters of evaluation and the influence between criteria for evaluating alternative fashion design schemes.

The integrated approach uses the advantages of all three methods: the Decision-Making Trial and Evaluation Laboratory (DEMATEL) can be used to analyse the interrelations between the major clusters of fashion design evaluation. The analytical network process can calculate the criterion weight that is adjusted based on the influence between different elements in the decision framework. The Visekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) determines the best fashion design by ranking a set of designs by using ten conflicting criteria.

Style is the decisive dimension because it is highly affected by other clusters. The comfort of the style is the most crucial criterion. “Veracious” is the best and most preferred design scheme.

The study develops the decisive cluster and criteria in designing a fashion design scheme. The proposed approach can be used as a decision analysis tool in fashion design and other fields and has various advantages (e.g. considering interrelations between clusters and influences between criteria, and ranking a set of alternatives), and therefore, is appropriate for practical circumstances.

The study explores how a market-like organizational system realizes efficient and/or effective development by investigating the efficiency/effectiveness trade-off in micro-level exchanges.

The study is motivated by two principles: reciprocity and similarity. Reciprocal benefits drive exchanges. Accordingly, two agents for a potential exchange should have different resources. However, differences in resources usually cause lack of trust, which hinders the efficient occurrence of exchanges. Alternatively, if two parties have similar resource positions, they can conduct an exchange efficiently. Nevertheless, the similarity makes the exchange less effective. Therefore, an efficiency/effectiveness trade-off exists in micro-level exchanges. To understand how different focuses on the efficiency/effectiveness trade-off shape the macro-level performance, the author develops a complex adaptive systems model for computer simulations.

The author finds that an efficiency-focus institution facilitates a market-like organizational system's rapid emergence but hinders the system's effective development.

The study develops a model of how a dyadic exchange happens (or not) between any two parties in a competitive and uncertain environment and how the micro-level exchanges aggregate, suggesting one specific way to understand the micro-to-macro process of a market-like organizational system's economic dynamism. Future research is expected to improve the model with different contingencies.

The study's findings suggest that the efficiency-focus institution and the effectiveness-focus institution should be used at different times in a market-like organizational system's development process.

The study investigates the macro-level consequences building upon the micro-level efficiency/effectiveness trade-off.

The purpose of this paper is to provide a better understanding of the development of intelligent agriculture (IA) in China, which is an important tendency in advancing the agricultural productivity in the coming era.

Considering publications as featured evidence of an emerging phenomenon, the authors review publications of IA. Specifically, the use of term, definition and examples of IA, both English and Chinese literature, and government policies of China are all reviewed. Additionally, the authors use basic statistical and thematic analysis to help synthesizing the literature and drawing conclusions. Findings from various sources of publications supplement with each other.

IA in China has shown three main characteristics: unbalanced geographic distribution, an early stage of the trend and attention mainly focused on a limited range of technologies. Compared with the development of IA in other countries, such as Japan, India and the USA, featured with diversified properties, similarities and differences of IA development in China and in other countries are also discussed.

This general review contributes by uncovering the emergence of IA, identifying its general definition with a comprehensive set of practical examples and pointing out the present characteristics and problems of IA development in China. The general review provides a necessary summary for the policy makers and researchers to have a systematic understanding of IA and better promote its future development. At last, the paper calls for a process-based strategy with different goals at different stages, a sustainable mechanism coordinated by multiple participants, and a localized consideration for relevant policy making.

Extreme support vector regression (ESVR) has been widely used in the design, analysis and optimization of engineering systems of its fast training speed and good computational ability. However, the ESVR model is only able to utilize one-fidelity information of engineering system. To solve this issue, this paper extends extreme support vector regression (ESVR) to a multi-fidelity surrogate (MFS) model which can make use of a few expensive but higher-fidelity (HF) samples and a lot of inaccurate but cheap low-fidelity (LF) samples, named ESVR-MFS.

In the ESVR-MFS model, a kernel matrix is designed to evaluate the relationship between the HF and LF samples. The root mean square error of HF samples is used as the training error metric, and the optimal hyper-parameters of the kernel matrix are obtained through a heuristic algorithm.

A number of numerical problems and three engineering problems are used to compare the ESVR-MFS model with the single-fidelity ESVR model and two benchmark MFS models. The results show that the ESVR-MFS model exhibits competitive performance in both numerical cases and practical cases tested in this work.

The proposed approach exhibits great capability for practical multi-fidelity engineering design problems.

A MFS model is proposed based on ESVR, which can make full use of the advantages of both HF data and LF data to achieve optimal results at same or lower cost.

This study proposes and demonstrates a novel approach to analyzing customer channel preferences and willingness-to-pay (WTP) in the dual sales channel (DSC) system involving direct online channels and conventional offline retailers, and to how the pricing decisions are made under specific game competition.

Questionnaire survey based on central composite experiment design was utilized to obtain primary data. The model for customer channel preferences and WTP was then built by using multinomial logistic regression. The propensity of a customer to make purchases in either channel estimated by using the logit model was inserted in the bilevel programming model to formulate and solve for the Stackelberg competition where the conventional retailer acted as a leader.

The study found that channel prices have nonlinear impacts on WTP and channel preference. The empirical results complement the mathematical formulation well where high-order own-price and cross-price effects on channel selection are generally not analytical tractable. Under the Stackelberg competition, the traditional retailer (as the leader) still achieves higher profits than the online facility.

The proposed framework provides an empirical approach that can easily address the competition model in the sales channel when complicated own-price or cross-price effects are present.

The present work provides a novel approach to analyze customer preference and WTP of the DSC systems. This alternative method simplifies the procedure for investigating and estimating price sensitivity, especially when the online and offline prices affect customer WTP and channel preferences nonlinearly. This model is also utilized in the game competition to facilitate data-driven price decision making to better formulate and understand real-world DSC problems.

The purpose of this paper is to study the flow patterns and particle-particle collisions during the sedimentation of multiple circular particles under gravity at intermediate Reynolds numbers through direct numerical simulations (DNS).

The previously developed lattice Boltzmann-direct forcing/fictitious domain (LB-DF/FD) method is adopted in this work to conduct DNS.

It is found that the number of particle-particle collisions display a linear growth at long times after an initial evolution, resulting in a constant collision rate, which also depends the initial arrangement.

The problem of particle-particle collisions during sedimentation with two kinds of particle density has not been considered before and it is of special importance in various industries.

The purpose of this paper is to study numerically the rheological properties of fiber suspensions flowing through turbulent pipe flows.

The work presented in this paper is derived the fluctuating equation for fiber orientation distribution function (FODF) in turbulent flows and solved using the method of characteristics. The FODF is predicted numerically. The numerical results of root-mean-square velocities generated by kinetic simulation sweeping model and are compared with the experimental data.

The fiber orientation distribution becomes wider with increasing Re. The components of the fourth-order orientation tensor increase with the increase of Re, and also increase along the radial direction and reach the maximum at the center line. The first normal stress difference is much less than the shear stress. For different Re the shear stress increases rapidly in the region far from the pipe center, and reaches its maximums at center, while the first normal stress difference decreases rapidly in the region far from the pipe center, and reaches its minimum at center finally.

By solving numerically the equation in a turbulent pipe flow with Reynolds number ranging from 2,500 to 1,000, the authors obtain the mean FODF which is in agreement with the experimental one qualitatively. Then the shear stress and first normal stress difference of suspensions are calculated based on the mean FODF.

From the intra- and inter-regional dimensions, this paper investigates the linkage between industrial agglomeration and inventory performance, and further demonstrates the moderating role of firm size and enterprise status in the supply chain on this linkage.

Using a large panel dataset of Chinese manufacturers in the Yangtze River Delta for the period from 2008 to 2013, this study employs the method of spatial econometric analysis via a spatial Durbin model (SDM) to examine the effects of industrial agglomeration on inventory performance. Meanwhile, the moderation model is applied to examine the moderating role of two firm-level heterogeneity factors.

At its core, this research demonstrates that industrial agglomeration is associated with the positive change of inventory performance in the adjacent regions, whereas that in the host region as well as in general does not significantly increase. Additionally, both firm size and enterprise status in the supply chain can positively moderate these effects, except for the moderating role of firm size on the positive spillovers.

In view of firm heterogeneity, managers should take special care when matching their abilities of inventory management with the agglomeration effects. Firms with a high level of inventory management are suited to stay in an industrial cluster, while others would be better in the adjacent regions to enhance inventory performance.

This paper is the first to systematically analyze the effects of industrial agglomeration on inventory performance within and across clusters, and confirm that these effects are contingent upon firm size and enterprise status in the supply chain. It adds to the existing literature by highlighting the spatial spillovers from industrial clusters and enriching the antecedents of inventory leanness.

This paper aims to explore the effects of director network on open innovation. As an informal institutional arrangement, the director network is an important source for the enterprise to obtain external information, which provide resource basis for open innovation. Chief Executive Officer (CEO) as the top of management team could make short-sighted decisions for personal interests; this paper also investigates the moderating role of CEO short-sightedness between director network and open innovation.

This paper takes 4,102 Chinese listed companies from 2007 to 2020 as the research sample. By introducing network centrality and structural hole to measure director network and using data mining to extract key words related to CEO short-sightedness from annual reports, this paper constructs several multiple linear regression models to analyze the impact of director network on open innovation and the moderating role of CEO short-sightedness.

The analysis finds that director network can facilitate corporate open innovation. Enterprises can acquire more external resources in high centrality and structural hole of director network and promote ability for corporate open innovation. The relationship between director network and open innovation is negatively moderated by CEO short-sightedness. When the level of corporate governance and analyst attention is high, the negative effect of CEO short-sightedness on the innovation effect of directors’ networks is suppressed.

This is the first empirical paper to investigate the promotion effect of director network on open innovation as well as the negative moderating role of CEO short-sightedness. The findings bring new perspectives to the open innovation and enlightenments for practical activities from social relationship aspect.