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This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.

The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.

From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.

Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

The spatial and non-spatial attributes are the two important characteristics of a spatial point, which belong to the two different attribute domains in many Geographic Information Systems applications. The dual clustering algorithms take into account both spatial and non-spatial attributes, where a cluster has not only high proximity in spatial domain but also high similarity in non-spatial domain. In a geographical dataset, traditional dual spatial clustering algorithms discover homogeneous spatially adjacent clusters suffering from the between-cluster inhomogeneity where those spatial points are described in non-spatial domain. To overcome this limitation, a novel dual-domain clustering algorithm (DDCA) is proposed by considering both spatial proximity and attribute similarity with the presence of inhomogeneity.

In this algorithm, Delaunay triangulation with edge length constraints is first employed to construct spatial proximity relationships amongst objects. Then, a clustering strategy based on statistical change detection is designed to obtain clusters with similar attributes.

The effectiveness and practicability of the proposed algorithm are illustrated by experiments on both simulated datasets and real spatial events. It is found that the proposed algorithm can adaptively and accurately detect clusters with spatial proximity and similar non-spatial attributes under the consideration of inhomogeneity.

Traditional dual spatial clustering algorithms discover homogeneous spatially adjacent clusters suffering from the between-cluster inhomogeneity where those spatial points are described in non-spatial domain. The research here is a contribution to developing a dual spatial clustering method considering both spatial proximity and attribute similarity with the presence of inhomogeneity. The detection of these clusters is useful to understand the local patterns of geographical phenomena, such as land use classification, spatial patterns research and big geo-data analysis.

The purpose of this paper is to explore the contemporary paradigm of business leadership vis-à-vis China’s reform and transitional context.

The paper employs an evidence-based approach to explore the business leadership issues influenced by economic reform and within the context of societal transition in China. A qualitative research method was adopted based on in-depth interviews with a number of middle managers from a variety of Chinese enterprises, including state-owned, domestic-private and foreign-invested enterprises. Content analysis of several rounds of interviews added depth to the data analysis.

The findings complement existing thoughts and illustrate concepts, issues, and characteristics not yet emphasized in mainstream literature. General patterns and associated characteristics of business leadership in China, as well as specific patterns associated with different forms of enterprise ownerships, are identified.

The study makes a timely and necessary contribution that enriches context-specific understandings of business leadership against the backdrop of surrounding economic, social, and cultural changes.

The study enriches understandings of commonalities and differences in leadership across the globe, facilitating working collaboratively to achieve common goals in a global community.

The study offers new insights into business leadership by linking contextual, personal, and cognitional factors together and demonstrates some unique characteristics of leadership styles in transitional economies like China.

This study aims to examine whether the newly available auditor tenure information is associated with non-GAAP earnings, as the recent requirement to disclose the initial year of auditor-client relationship in audit reports may give the impression that longer auditor tenure may be related to lower audit quality.

Using a sample of firm-quarters from 2017 to 2020, the authors conduct both univariate and regression analyses. We use hand-collected data for auditor tenure, SEC comment letters, and non-GAAP variables.

First, the authors find that the likelihood of disclosing non-GAAP earnings monotonically increases with auditor tenure on a univariate basis. Second, auditor tenure is negatively associated with aggressive non-GAAP reporting. Third, the authors document evidence of aggressive reporting in general; that is, items excluded in calculating non-GAAP earnings are associated with future performance. However, the association declines with longer auditor tenure. Finally, the authors report evidence that the likelihood of receiving an SEC comment letter that contains non-GAAP comments decreases with longer auditor tenure.

The results show that regulators need to consider both GAAP and non-GAAP disclosures’ costs and benefits when enacting auditor tenure regulation. Investors can benefit from the findings in evaluating the quality of non-GAAP earnings. The findings are also relevant to the SEC when allocating limited resources in monitoring non-GAAP reporting.

To the best of the authors’ knowledge, this is the first study showing that auditor tenure is associated with the quality of non-GAAP earnings. Given that financial reporting quality should be understood as a comprehensive system comprising both mandatory and voluntary disclosures, this study complements the literature that examines the effect of auditor tenure on financial reporting quality using GAAP reporting.

Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view.

To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model.

The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency.

The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds.

The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice.

This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.

The purpose of this paper is to investigate the equivalent control authority of the conventional and circulation control (CC) wing of the aircraft and assess the energy expenditure and aerodynamic efficiency of the CC wing.

Four target cases with different flap deflection angles θ are set in advance for the conventional wing, and then a series of cases with different jet momentum coefficients Cμ are set for the CC wing. The lift, drag and momentum coefficient curves of the CC wing are compared to those of the four conventional wing cases. The curves with the best agreement are selected to establish the corresponding relation between θ and Cμ. The energy expenditure of the CC system is analyzed. The concept of equivalent lift-to-drag ratio for the CC wing is introduced to compare the aerodynamic efficiency with the conventional wing

The control authority of the conventional wing at θ = 0º, 10º, 20º, 30º are equivalent to the control authority of the CC wing with Cµ = 0.0, 0.005, 0.009 and 0.012. The CC system is more efficient at small Cµ than large Cµ.

This study could contribute to the application of the CC system on flapless aircrafts.

The corresponding relation between θ and Cµ is established by matching the equivalent control authority between the conventional wing and CC wing.

The purpose of this paper is to improve the accuracy of evaluation efficiency by constructing parallel structures considering the main components of industrial pollutants, and then to consider some external influence factors to eliminate random errors.

In this paper, data transformation has been used to deal with undesirable output, and a model with a parallel structure based on the three-stage data envelopment analysis model to calculate the efficiency scores of different division in pollution treatment has been composed.

The analysis shows that the external environmental factors and random factors of the economy and society greatly affect the efficiency of industrial pollutant treatment; moreover, there is an imbalance between regions in China in the treatment of industrial pollutants.

Optimal improvement requires each province to take targeted measures to improve its efficiency of pollutant treatment measures, which are tailored to specific situations and determined by efficiency analysis in this paper.

The purpose of this paper is to describe the design and initial implementation of a lesson study network in the US intended to support implementation of the Common Core State Standards (CCSS).

Participant observation and artifact collection document the development of the teaching through problem solving (TTP) network over a 14-month period.

The TTP network draws heavily on Japanese practices (e.g. lesson study) and Japanese materials (e.g. coherent, focussed mathematics curriculum) to support changes envisioned in the US CCSS related to students’ mathematical practices and dispositions. The reasons for choice of these key Japanese features are explicated, and teachers’ initial reactions described.

The design shows promise for combining teacher “ownership” with implementation of high-quality approaches designed by others; and allowing instructional innovations developed in Japan to flow into US practice. TTP in mathematics has persistently resisted implementation in the US, so the network is designed to target a central problem in implementing the CCSS.

A method for instructional innovations to spread from classrooms in one country to another is suggested.

More and more older adults begin to use the mobile internet to obtain information. However, the quality of information obtained through mobile internet by older adults is hard to be guaranteed. The purpose of this paper is to study the role of family support when older adults obtain information from mobile internet.

This study conducted a survey of 263 older adults who owned mobile internet devices such as smartphones or tablet PCs. The theory hypotheses are tested using partial least squares techniques.

For older adults, family support is the influencing factor of mobile internet literacy improvement. Family emotional support has stronger impacts on the improvement both of mobile internet skill literacy and of mobile internet information literacy than family cognitive support has. Furthermore, the improvement of both mobile internet skill literacy and of mobile internet information literacy hs positive impacts on the quality improvement of obtained information by older adults.

This paper gives advice on how family members can support older adults during their obtaining information from mobile internet to improve their mobile internet literacy and quality of obtained information.

This study examines the factors that influence mobile internet literacy and quality of obtained information among older adults from the perspective of family support in the Chinese mobile internet context. The research results enrich the internet literacy theory and the information quality theory.