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Parallelogram linkages are used to increase the stiffness of manipulators and allow precise control of end-effectors. They help maintain the orientation of connected links when the manipulator changes its position. They are implemented in many palletizing robots connected with binary, ternary and quaternary links through both active and passive joints. This limits the motion of some joints and hence results in relative and negative joint angles when assigning coordinate axes. This study aims to provide a simplified accurate model for manipulators built with parllelogram linkages to ease the kinematics calculations.

This study introduces a simplified model, replacing each parallelogram linkage with a single (binary) link with an active and a passive joint at the ends. This replacement facilitates countering motion while preserving subsequent link orientations. Validation of kinematics is performed on palletizing manipulators from five different OEMs. The validation of Dobot Magician and ABB IRB1410 was carried out in real time and in their control software. Other robots from ABB, Yaskawa, Kuka and Fanuc were validated using control environments and simulators.

The proposed model enables the straightforward derivation of forward kinematics and transforms hybrid robots into equivalent serial-link robots. The model demonstrates high accuracy streamlining the derivation of kinematics.

The proposed model facilitates the use of classical methods like the Denavit–Hartenberg procedure with ease. It not only simplifies kinematics derivation but it also helps in robot control and motion planning within the workspace. The approach can also be implemented to simplify the parallelogram linkages of robots with higher degrees of freedom such as the IRB1410.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

This study investigates theoretical relationships among personality characteristics, preferences for different types of rewards and the propensity to choose a job in auditing by management-related higher education students. Specifically, the authors consider motivation, locus of control (internal and external) and self-efficacy (SE) as personality characteristics and financial, extrinsic, support and intrinsic as types of rewards.

Data were collected through a questionnaire targeted at management-related higher education students in Portugal. Partial least squares structural equation modelling was used to analyse the data.

The full sample results show that different types of motivation, locus of control and SE are related to different reward preferences. The authors also find a positive association between a preference for extrinsic rewards and the propensity to choose a job in auditing. Moreover, when the authors consider the role of working experience in the model, the authors find that the reward preferences that drive the choice of an auditing job differ according to that experience.

This study enriches the literature by assessing preferences for different types of rewards, considering multiple personality characteristics and a comprehensive set of rewards. Furthermore, the authors identify the reward preferences that drive the choice of an auditing career. This knowledge empowers auditing firms to devise recruitment strategies that resonate with candidates’ preferences, which boosts the capacity of these companies to attract new auditors.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

This paper aims to empirically investigate the impact of the carbon intensity constraint policy (CICP) on green innovation.

This study takes the implementation of the CICP as a quasi-natural experiment and uses a quasi–difference-in-difference method to investigate the impact of the CICP on firm green innovation from a microeconomic perspective.

The CICP significantly limits the quality of firms’ green innovation. Among the range of green patents, the CICP distorts only patents related to CO₂ emissions. The inhibitory effect is more pronounced in non-state-owned enterprises and heavily polluting firms. R&D investment and green investor are identified as the main mechanism.

These findings provide evidence for the influence of the CICP on firm green innovation, which can guide policymakers in China and other emerging economies that prioritize carbon intensity constraint targets and the improvement of relevant auxiliary measures.

Governments and firms should have a comprehensive understanding of environmental policies and corporate behavior and need to mitigate the negative impact through a combination of measures.

This study contributes to the literature by providing additional empirical evidence regarding the two opposing sides of the ongoing debate on the positive or negative effects of CICP. It also provides new evidence on the policy effect of the CICP on firm green innovation, together with its mechanisms and heterogeneous influences.

This article summarizes the international scientific research output of global forest product models, infers future research trends and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

In 1999, Joseph Buongiorno, a scholar at the University of Wisconsin in the United States of America, proposed the global forest products model (GFPM), which was first applied to research in the global forestry sector. GFPM is a recursive dynamic model based on five assumptions: macroeconomics, local equilibrium, dynamic equilibrium, forest product conversion flow and trade inertia. Using a certain year from 1992 to present as the base period, it simulates and predicts changes in prices, production and import and export trade indicators of 14 forest products in 180 countries (regions) through computer programs. Its advantages lie in covering a wide range of countries and a wide variety of forest products. The data mainly include forest resource data, forest product trade data, and other economic data required by the model, sourced from the Food and Agriculture Organization (FAO) of the United Nations and the World Bank, respectively.

Compared to international quantitative and modeling research in the field of forest product production and trade, China's related research is not comprehensive and in-depth, and there is not much quantitative and mathematical modeling research, resulting in a significant gap. This article summarizes the international scientific research output of global forest product models, infers future research trends, and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

On the basis of summarizing and analyzing the international scientific research output of GFPM, sorting out the current research status and progress at home and abroad, this article discusses potential research expansion directions in 10 aspects, including the types, yield and quality of domestic forest product production, international trade of forest products, and external impacts on the forestry system, in order to provide new ideas for global forest product model research in China.

The information used in the case study was obtained from secondary sources, such as internal documents, reports, news, and organization websites. Three of the four authors played a hands-on role in the case.

The COVID-19 pandemic exacerbated the global challenge of hiring and retaining health-care workers. To address its own challenges, Mayo Clinic decided to fundamentally transform its 30-year-old tuition assistance program: from a model centered on the premise that tuition assistance was an employee benefit for professional development purposes, to one that was more driven to meet the business needs of the employer by preparing internal talent for important roles throughout the institution. Herein, this case study first describes how the COVID-19 pandemic impacted health-care organizations like Mayo Clinic. Next, this study provides details on the original employee tuition assistance program, and then, focuses on the reasons for its need to be changed. Afterward, this study introduces the new tuition assistance programs. Finally, this study follows with examples of how both Mayo Clinic and its employees navigated through initial challenges, such as resistance to change and lack of engagement. In sum, this case study provides critical insight into designing workforce education programs that provide professional development for meeting the workforce needs of the organization.

This case can be used as teaching material in relevant undergraduate- and MBA-level courses, such as human resource management, human resource development and compensation and benefits. This case allows students to critically analyze workforce education programs (e.g. tuition assistance programs) and to plan how to strategically align those with the workforce needs of the organization.

This study aims to examine whether firms that appear to exhibit high sustainable outputs are more likely to pay higher audit fees than firms without such outputs.

The sustainability outputs are measured using a sustainable product portfolio consisting of four products: clean energy products, eco-design products (EDP), environmental products (EP) and sustainable building projects (SBP). The audit fee variable is measured by the natural logarithm of the total amount of audit fees. The study tests two models of the association between these outputs and audit fees; Model 1 tests this association in the absence of the moderating variable (sustainability committee), and Model 2 tests the association in the presence of the moderating variable.

An analysis of data on 261 European firms from the Refinitiv Eikon database from 2010 to 2019 shows that high sustainability outputs are significantly and positively associated with audit fees. More importantly, this association is moderated by the presence of a board-level sustainability committee, suggesting that this type of committee reflects a factor considered by auditors in their audit risk assessment practices. The findings indicate that in Model 1, one (EP) out of four variables has a significant and positive association with audit fees, while in Model 2 and in the presence of sustainability committee, two variables (EP and EDP) have a significant and negative association with audit fees. However, the robust analysis shows that three variables (EP, EDP and SBP) have significant and negative associations with audit fees.

The study findings have important implications for policymakers, auditors and firms’ managers. For policymakers, the findings provide support for the argument that sustainable attitudes incentivise firms to manage sustainable product profiles more effectively. As such, policymakers should incentivise firms to establish a sustainability committee and regulate its role and responsibilities. Auditors should coordinate with the sustainability committee to facilitate audit efforts and reduce audit fees.

Understanding the relationship between sustainable products and audit fees will allow firms to improve their portfolio of sustainable products. In addition, other social implications of this study relate to improving relationships with society by establishing a sustainability committee that is responsible to communicate with that society.

The results support the argument that firms should manage sustainable product portfolios more effectively. In addition, the results of the study highlight the importance of a new variable as a moderator, the sustainability committee, which has not been examined before.

This research draws on drive reduction theory and mental accounting theory to understand how the prospect of reselling used items can influence consumer feelings of consumption guilt and impact their willingness to purchase new products.

We conducted two studies with between-subjects designs to explore this relationship. In Study 1, we examined the correlation between consumers' perceived guilt and their willingness to buy a new product, considering their awareness of the product’s resale potential. Study 2 delved into the aspect of reselling a similar old product already owned by the consumer.

The findings suggest three key insights. First, consumers' awareness of resale potential significantly affects their guilt perception and purchasing decisions. Second, the resale reference price (RRP) can decrease guilt perception but increase the intention to buy a new product. Lastly, when consumers are aware of the resale value of a previously owned product that is similar to the desired new product, the effect of the RRP on their purchasing intent is mediated by consumer guilt.

This research fills a theoretical gap by empirically exploring the emotional motivations behind consumer resale behavior. It presents a novel perspective on how resale activities can shape feelings of guilt and impact purchasing decisions. This offers important implications for understanding the dynamics of consumer behavior in the second-hand market.