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The purpose of this paper is to explore what organizational adaptability means in the digitized context and to discuss how manufacturing companies achieve organizational adaptability during the digital transformation process.

By conducting semi-structured interviews and acquiring archive data from a typical Chinese manufacturing company, this paper gathers extensive data. Based on this, a single-case study methodology is used to investigate organizational adaptability in digital transformation.

This study identifies the process by which companies achieve organizational adaptability during digital transformation and deconstructs organizational adaptability into three dimensions: structural adaptability, operational adaptability and governance adaptability. This study also explores how organizational adaptability is affected by digital capabilities.

This study proposes a process model to demonstrate how organizational adaptability may be attained during digital transformation and redefines organizational adaptability in the context of digitization.

The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid colliding with other objects and achieve accurate movements. Trajectory planning algorithms are the soul of motion control of industrial robots. A predefined space trajectory can let the robot move through the desired spatial coordinates, avoid colliding with other objects and achieve accurate movements.

The mathematical expressions of the proposed algorithm are deduced. The speed control, position control and orientation control strategies are realized and verified with simulations, and then implemented on a six degrees of freedom (6-DOF) industrial robot platform.

A fixed-distance trajectory planning algorithm based on Cartesian coordinates was presented. The linear trajectory, circular trajectory, helical trajectory and parabolic trajectory in Cartesian coordinates were implemented on the 6-DOF industrial robot.

A simple and efficient algorithm is proposed. Enrich the kind of trajectory which the industrial robot can realize. In addition, the industrial robot can move more concisely, smoothly and precisely.

3D printing based on additive manufacturing has advantages in manufacturing products with high geometrical complexity. However, there are many limitations to print plastic products with the existing commercial 3D printers. The polymer materials processing industry needs new devices which can satisfy the trend of processing individual units and small batch sizes of plastic parts.

In this study, a freeform fabrication system with the method of polymer melt droplet deposition is proposed. The performance of this system under different conditions was studied by changing the operating parameters. Furthermore, the dimensional uniformity of droplets and their deposition process are analyzed, and a plastic sample was fabricated with this system as an example.

The results show a clear correlation between the processing parameters and the droplet diameter. In the experiment for examining the dimensional uniformity of the droplet, the droplets become spindles, and there appears a melt filament between the droplets. The variation of the droplet’s diameters is within 5 per cent. Furthermore, a successfully processed rectangular plastic sample verified the feasibility of this technology for the printing of plastic products.

A freeform fabrication system with polymer melt droplet deposition is proposed, which can process a wide variety of materials in the form of standard granulates like injection molding or extrusion. Based on the principle of droplet deposition, multi-component or colorful materials can be printed.

This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.

The authors propose a divide-and-combine (DAC) approach for generating different instances of TMT that can be used in repeated assessments with nearly no discernible practice effects. In the DAC approach, partial trails are generated separately in different layers and then combined to form a complete TMT trail.

The proposed approach was implemented in a computerized test application called iTMT. A pilot study was conducted to evaluate iTMT. The results show that the instances of TMT generated by the DAC approach had an adequate level of difficulty. iTMT also achieved a stronger construct validity, higher test–retest reliability and significantly reduced practice effects than existing computerized tests.

The preliminary results suggest that iTMT is suitable for long-term monitoring of cognitive abilities. By supporting self-assessment, iTMT also can help to crowdsource the assessment processes, which need to be administered by healthcare professionals conventionally, to the patients themselves.

The purpose of this paper is to seek a surfactant or template-free, simple and green method to fabricate NiO nanobelts and to find an effective technique to detect the ethanol vapor at room temperature.

NiO nanobelts with high aspect ratio and dispersive distribution have been synthesized by a template-free hydrothermal reaction at 160°C for 12 h. The products are studied by X-ray diffraction (XRD), energy dispersive spectroscopY, scanning electron microscopy, atomic force microscopy, high-resolution transmission electron microscopy, selective area electron diffractio and X-ray photoelectron spectroscopy. In particular, the room-temperature ethanol sensitivity of NiO nanobelts is investigated by the surface photo voltage (SPV) technique.

The prepared NiO nanobelts is single crystalline bunsenite structure with the length of approximately 10 μm and the diameter of approximately 30 nm. The atomic ratio of “Ni” to “O” is 0.92:1. When the concentration of ethanol vapor reaches 100 ppm, the sensitivity of NiO nanobelts is 7, which can meet the commercial demanding of ethanol gas sensor.

The NiO nanobelts can be obtained by a template-free, simple and green hydrothermal reaction at 160°C for 12 h. The NiO nanobelts-based gas sensor is a promising candidate for the application in ethanol monitoring at room temperature by SPV technique.

The purpose of this paper is to find an effective route to fabricate high transparent top electrode in quantum dots light-emitting diodes (QLEDs).

Al-doped ZnO (AZO) top cathode with high transparency have been deposited by an atomic layer deposition (ALD) method at 140°C for 1 h. The products are studied by UV-vis spectrometer and atomic force microscopy (AFM). The electroluminescence spectra of QLED are recorded using an Ocean Optics high-resolution spectrometer (HR4000). The devices were measured under ambient conditions without encapsulation.

The AZO-based QLED shows excellent performance with high luminance and current efficiency.

The AZO obtained by ALD method is a promising cathode candidate for application in QLEDs.

Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating.

In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor data from a smart home environment and analyzes the user’s contextual information through a computational abstract argumentation-based activity classifier.

Based on user’s different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices.

This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.

The purpose of this paper is to establish a simplified model of the closed hydrostatic guideway for the rapid analysis of static and dynamic characteristics. Further, the influence of compressibility and dynamic frequency are taken into consideration in the new dynamic model.

The new model is based on the second kind of Lagrange equation. In this model, the closed hydrostatic guideway is supported by 12 pads, and each oil pad is equivalent to a nonlinear spring-damper system. The equivalent spring coefficient and damper coefficient of the oil pad are extracted by the three different equivalent methods. Finally, the validation experiments of step load response and dynamic stiffness are conducted on a hydrostatic guideway.

For solving the step response, the linear spring-damper model and the nonlinear spring-damper Model 1 are better than the nonlinear spring-damper Model 2. The accuracy of the three methods are very high for static stiffness calculation. For the calculation of dynamic stiffness, the nonlinear spring-damper Model 2 is better than the nonlinear spring-damper Model 1. The linear spring-damper model has low precision for dynamic stiffness calculation, especially at high frequency. The accuracy of the new model is validated by experiments.

The equivalent method of nonlinear spring-damper system has higher accuracy. Different equivalent methods should be adopted for different load types. The computational speeds of the new dynamic model with the three methods are much better than finite element method (about ten times).

The purpose of this paper is to propose a consensus method for multi-attribute group decision-making (MAGDM) problems based on preference-approval structure and regret theory, which can improve the efficiency of decision-making and promote the consensus level among individuals.

First, a new method to obtain the reference points based on regret theory and expert weighting method is proposed. Second, a consensus reaching method based on preference-approval structure is proposed. Then, an adjustment mechanism to further improve the consensus level between individuals is designed. Finally, an example of the assessment of elderly care institutions is used to illustrate the feasibility and effectiveness of the proposed method.

The feasibility and validity of the proposed method are verified by comparing with the advanced two-stage minimum adjustment method. The compared results show that the proposed method is more consistent with the actual situation.

This paper presents a consensus reaching method for MAGDM based on preference-approval structure, which considers the avoidance behaviors of individuals and reference points. Decision makers (DMs) can use this approach to rank and categorize alternatives while further increasing the level of consensus among them. This can further help determine the optimal alternative more efficiently.

A new MAGDM problem based on the combination of regret theory and individual reference points is proposed. Besides, a new method of obtaining experts' weights and a consensus reaching method for MAGDM based on preference-approval structure are designed.

Why would a hospitality or tourism enterprise’s talent program backfire to demotivate interns from engaging in their jobs? This study aim to synthesize theoretical strands from the self-determination theory, person–environment fit theory and conservation of resources theory to investigate the predictors of perceived person–job fit and how such a fit causes changes in interns’ job motivation over time.

A four-wave longitudinal study was conducted. The four waves of data obtained from over 251 interns in China were analyzed using latent growth curve modeling.

The findings demonstrate that abusive co-worker treatment moderated the impact of perceived negative social status and perceived overqualification on perceived person–job fit. Moreover, perceived person–job fit is a significant predictor of the initial level of job motivation and flattens the decrease in job motivation over time. These findings demonstrate that interns’ job motivation generally decreased over time, and perceived person–job fit may help dampen the change trajectory of job motivation.

This study contributes to the practice of education and organizations in hospitality and tourism management by advocating for better interventions to improve interns’ work experience and motivations. Also, organizations can create team-building opportunities and promote teamwork that contributes to the formation of cohesive relationships and improve personal bonding.

This longitudinal inquiry conducted in China underscores the perils of hospitality/tourism internship by synthesizing a framework based on the theoretical strands germane to person–environment fit, resource conservation and self-determination. It uncovers the dark side of internship – not only due to mismanaged internship experience, but also because it could backfire to create a demotivational spiral that may ultimately drive potential talents away from hospitality/tourism organizations and industry.