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This paper aims to present a complete relative pose error model for robot calibration, considering both the relative distance error and the relative rotation error of the robot end-effector, which can improve calibration accuracy.

In this paper, the relative distance error model and the relative rotation error model of robot calibration are derived by ignoring high-order nonlinear errors, and the two models form into a complete relative pose error model. Besides, mathematical expectation of the nonlinear errors is calculated, indicating that they have little influence on calibration accuracy.

Comparative experiments have indicated that the proposed complete relative pose error model does better in robot calibration than only the distance error model.

The main contribution of this paper lies in the derivation of the relative rotation error model, which helps to form a complete relative pose error model for calibration. The proposed method improves calibration accuracy, with avoiding identifying the transformation matrix between the measurement system frame and the robot base frame.

By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.

First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.

Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.

This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

Fundamental literature exists on the employment of diverse information technology (IT) innovations relied on utility computing, a little experimental literature exists on cloud computing adoption by medium enterprises. So, this essay aims to analyze the determinants of the acceptance of cloud computing in medium-sized organizations. It also targets the impact of cloud-depended services on employers' talent management in the analysis areas of research reports, hypotheses and frameworks used by them.

Cloud computing is a novel and notable development in the network application field with a novel IT viewpoint. The present investigation aims to assist and enrich the scientific argument regarding the phenomenon nominated cloud computing from a managerial perspective. A quantitative study design was utilized to gather and analyze the data. In total, 345 employees from different medium enterprises reported their perspectives via an online survey. Partial least squares was used to evaluate the model of the study. The investigation was performed from April 2020 to November 2020.

As expected, the empirical analysis results revealed that cloud computing adaption drivers positively and significantly associated with talent management. The results showed that organizational level is the most important factor in the effectiveness of talent management. Further, this study established a cloud strategy that moderates the relationships between cloud computing adaption drivers and talent management. As a general result, organization managers must implement cloud computing to improve organizational performance, reduce costs, enhance organizational innovation and reduce repetitive work. So, international trade facilitates and helps the country's economy.

There are still some drawbacks of this analysis that require addressing the findings. Initially, the authors gathered a country's data. Second, by considering multiple significant structures from four aspects, they established the study model. Third, utilizing one-time cross-sectional data, the suggested model was evaluated. As a proposal, future researchers could investigate cloud computing adoption drivers' outcomes within other organizations.

This research presents a straightforward and easy model for understanding the cloud's effect on employee talent management. By systematizing the unrelated studies on the subject and organizing those contributions into strong managerial literature paradigms, such an aim has been accomplished.

This paper aims to explore product pricing and green promotion effort policies and further analyzes the influences of financing interest rate, green promotion effort and free-riding behavior on the optimal strategies.

Research will be conducted with the aid of Stackelberg game research method, considering that the manufacturer has financial constraints and financing from e-commerce platform, and consumers have dual preferences, based on the two models of no green promotion effort for physical store and green promotion effort for physical store to explore dual-channel green supply chain strategies.

This research puts forward the following findings, in the two models: the rise in financing interest rate leads to an increase in wholesale and selling prices of dual channels and a decrease in demand of dual channels. The green promotion effort has a positive impact on wholesale prices, selling prices and demand of dual channels. The rise of free-riding rate makes offline wholesale and selling prices fall, whereas online wholesale and selling prices rise.

This research results can provide reference for the decision-making in the context of supply chain financing and free-riding.

Production and transportation of precast components, as two continuous service stages of a precast plant, play an important role in meeting customer needs and controlling costs. However, there is still a lack of production and transportation scheduling methods that comprehensively consider delivery timeliness and transportation economy. This article aims to study the integrated scheduling optimization problem of in-plant flowshop production and off-plant transportation under the consideration of practical constraints of customer order delivery time window, and seek an optimal scheduling method that balances delivery timeliness and transportation economy.

In this study, an integrated scheduling optimization model of flowshop production and transportation for precast components with delivery time windows is established, which describes the relationship between production and transportation and handles transportation constraints under the premise of balancing delivery timeliness and transportation economy. Then a genetic algorithm is designed to solve this model. It realizes the integrated scheduling of production and transportation through double-layer chromosome coding. A program is designed to realize the solution process. Finally, the validity of the model is proved by the calculation of actual enterprise data.

The optimized scheduling scheme can not only meet the on-time delivery, but also improve the truck loading rate and reduce the total cost, composed of early cost in plant, delivery penalty cost and transportation cost. In the model validation, the optimal scheduling scheme uses one less truck than the traditional EDD scheme (saving 20% of the transportation cost), and the total cost can be saved by 17.22%.

This study clarifies the relationship between the production and transportation of precast components and establishes the integrated scheduling optimization model and its solution algorithm. Different from previous studies, the proposed optimization model can balance the timeliness and economy of production and transportation for precast components.

The purpose of this study is to examine the effect of the religiosity of the chief executive officer (CEO) on Indonesian banks’ performance.

The research method used was a review of the annual reports of banking companies in Indonesia from 2015 to 2019 and a web-based search to determine the religiosity of the CEOs. This study comprised 88 banking companies in Indonesia that come under the supervision of the Financial Services Authority.

The results of this study show that banks led by religious CEOs had better financial performance, as measured by their ROA and ROE, than those led by not very spiritual CEOs. These results indicate the importance of religiosity in organizations, especially at the top management level, for achieving better bank performance.

This research results show that religiosity plays an essential role in the banking business sector. This research adds to the literature on CEOs’ characteristics based on their religiosity and the concomitant effect on banking performance.

This study shows how individual religious beliefs influence the corporate behavior of top management, particularly the CEOs, and why this is crucial for organizational decision-making. This study measures an individual's religiosity (i.e. a CEO) based on that individual's actions in their workplace environment.

This paper analyzes the advance selling and pricing strategies of fresh products supply chain where the e-retailer provides wholesale contract or agency contract to the fresh products supplier.

This paper constructed a two-period sequential-move game of fresh products supply chain members.

This analysis showed that the supply chain members had different preferences for contracts under different market conditions. The advance selling of fresh products was not a decision of the seller, but also required the support of other supply chain members. And the advance selling strategy was not always beneficial to all supply chain parties. Under the two contracts, there were market conditions in which the profits of supply chain members were Pareto-improved through the implementation of advance selling.

The model presented in this study focuses solely on the context of monopoly, overlooking the competition from alternative suppliers or retailers. Consequently, exploring the competitive landscape within the fresh products supply chain, particularly in relation to pre-sale pricing, emerges as a crucial avenue for further investigation. By employing empirical research methods, valuable insights are gleaned, thereby significantly augmenting the existing body of relevant theories.

The decision to pre-sell fresh products should be based on market conditions. Supply chain members can control production costs and fresh products circulation losses to maximize profits.

From the perspective of game theory, this study analyzed the optimal advance selling and pricing strategies of fresh products supply chain members under two kinds of contracts. These results can provide practical implications for fresh products suppliers and e-retailers.

This study discusses the evolution of supply chain and the growing importance of dual marketing strategies. To understand the concept of dual marketing, we present a scenario faced by property developers in Malaysia on the impact of public policy on dual marketing strategy. This study is to uncover (1) the reasons why and how property developers adopt dual marketing strategy, (2) the impact of housing policy on the developers' dual marketing strategy and how they strategise to cope with the policy.