Search results

Over the past decade, artificial intelligence (AI) technologies have rapidly advanced organizational management, with many organizations adopting AI-based algorithms to enhance employee management efficiency. However, there remains a lack of sufficient empirical research on the specific impacts of these algorithmic management practices on employee behavior, particularly the potential negative effects. To address this gap, this study constructs a model based on the psychological ownership theory, aiming to investigate how algorithmic management affects employees’ knowledge hiding.

This study validates the model through a situational experiment and a multi-wave field study involving full-time employees in organizations implementing algorithmic management. Various analytical methods, including analysis of variance, regression analysis and path analysis, were used to systematically test the hypotheses.

The study reveals that algorithmic management exerts a positive indirect influence on knowledge hiding through the psychological ownership of personal knowledge. This effect is particularly pronounced when employees have lower organizational identification, highlighting the critical role of organizational culture in the effectiveness of technological applications.

This study is among the first empirical investigations to explore the relationship between algorithmic management and employee knowledge hiding from an individual perception perspective. By applying psychological ownership theory, it not only addresses the current theoretical gap regarding the negative effects of algorithmic management but also provides new theoretical and empirical support for the governance and prevention of knowledge hiding within organizations in the context of AI algorithm application. The study highlights the importance of considering employee psychology (i.e. psychological ownership of personal knowledge) and organizational culture (i.e. organizational identification) under algorithmic management. This understanding aids organizations in better managing knowledge risks while maximizing technological advantages and effectively designing organizational change strategies.

The purpose of this study is to present a highly stretchable and flexible strain sensor with simple and low cost of fabrication process and excellent dynamic characteristics, which make it suitable for human motion monitoring under large strain and high frequency.

The strain sensor was fabricated using the rubber/latex polymer as elastic carrier and single-walled carbon nanotubes (SWCNTs)/carbon black (CB) as a synergistic conductive network. The rubber/latex polymer was pre-treated in naphtha and then soaked in SWCNTs/CB/silicon rubber composite solution. The strain sensing and other performance of the sensor were measured and human motion tracking applications were tried.

These strain sensors based on aforementioned materials display high stretchability (500 per cent), excellent flexibility, fast response (approximately 45 ms), low creep (3.1 per cent at 100 per cent strain), temperature and humidity independence, superior stability and reproducibility during approximately 5,000 stretch/release cycles. Furthermore, the authors used these composites as human motion sensors, effectively monitoring joint motion, indicating that the stretchable strain sensor based on the rubber/latex polymer and the synergetic effects of mixed SWCNTs and CB could have promising applications in flexible and wearable devices for human motion tracking.

This paper presents a low-cost and a new type of strain sensor with excellent performance that can open up new fields of applications in flexible, stretchable and wearable electronics, especially in human motion tracking applications where very large strain should be accommodated by the strain sensor.

This research aims to investigate how entrepreneurial orientation influences a firm’s differentiation–cost advantage ambidexterity (DCAA) and performance indirectly through dynamic capabilities, while also investigating the impact of the interactive effect of the level and consistency of entrepreneurial orientation on dynamic capabilities. The goal of this study is to better understand the importance of consistently following an entrepreneurial orientation, as well as the linkage of such a consistently implemented strategy upon gaining both a cost and differentiation positioning enhancement.

Two empirical studies are conducted to test the proposed hypotheses – one longitudinal with multiple forms of data (i.e. text data, survey data and archival data) from 100 Taiwanese electronics firms and the other using primary data from a survey of senior managers.

Entrepreneurial orientation improves dynamic capabilities, which in turn promote superior DCAA and enhanced firm performance. In addition, as captured through a unique measure of consistency allowed through computer-aided text analysis, the results indicate that the effect of entrepreneurial orientation on dynamic capabilities is amplified when a firm consistently adopts entrepreneurial decisions and actions.

The specific context was a sample of electronics firms in Taiwan. This limits the generalization of findings, as would be possible with assessing the hypotheses in other industries.

This research clearly demonstrates the significance of consistency in pursuing a strategic orientation. The consistent support and deployment of resources facilitates an organization’s achieving positive outcomes associated with an entrepreneurial orientation.

While entrepreneurial orientation contributes to firm performance, extant knowledge on the internal process through which entrepreneurial orientation affects performance is relatively limited. The findings not only highlight the full mediating role of dynamic capabilities and DCAA, but also shed light on the importance of consistency in entrepreneurial orientation over time.

This study proposes a design automation system that integrates traditional segmental design processes into a solid unified system composed of need assessment, computer aided design, computer aided engineering and rapid prototyping. The system utilizes the computer network in conjunction with the quality function deployment technique coupled with a well designed expert system to precisely transform customers’ needs into producible product specification. The product is then displayed using a three‐dimensional representation and simulated through numerical analysis using a finite element method. The resulting feasible design alternative is finally linked to the rapid prototyper to produce the sample object. The use of the system is believed to greatly reduce R&D cost and significantly shorten the product design cycle, while closely meeting the customer’s needs.

This study aims to investigate the effect of coatings prepared by the addition of copper-aluminum alloy powder on the corrosion behavior of 90/10 copper-nickel alloy.

Coatings of copper-aluminum alloy powder at different contents (Wt.% = 50%, 60%, 70% and 80%) were prepared by the high-temperature heat treatment process. The microstructure and component of the coatings were characterized by scanning electron microscope, X-ray diffraction, energy dispersive spectrometer and X-ray photoelectron spectroscopy. The electrochemical properties of the coating were explored by electrochemical impedance spectroscopy.

The results show that the aluminized layer was successfully constructed on the surface of 90/10 copper-nickel alloy, the composition of the coating was composed of copper-aluminum phase and aluminum-nickel phase, the existence of the aluminum-nickel phase was formed by the diffusion of Ni elements within the substrate and because of the diffusion, the Al-Ni phase was distributed in the middle and bottom of the coating more. The Al-Ni phase is considered to be the enhanced phase for corrosion resistance. When the copper-aluminum alloy powder content is 70 Wt.%, the corrosion resistance is the best.

The enhancement of corrosion resistance of 90/10 copper-nickel alloy by the copper-aluminum alloy powder was revealed, the composition of the aluminized layer and the mechanism of corrosion resistance were discussed.

The purpose of this empirical paper is to identify the role of social networking information (SNI) on job candidates' pre-employment background checking (PBC) process. SNI was further divided into three elements: perceived availability of information (PAI), perceived accuracy of information (PACI) and perceived reliability of information (PRI). In addition, the authors employed two mediating variables: perceived benefit (PB) and organizational branding (OB) to study the influence of each element of SNI on PBC.

The authors used primary data collected from a valid sample of 465 using a structured questionnaire survey selected through purposive sampling. For descriptive analysis, SPSS 24 and for testing the hypothesized relationships, structural equation modeling technique (with AMOS 24) were utilized.

The results indicated that only PAI had strong positive influence on PBC. The other two independent variables: PACI and PRI had insignificant positive influence on PBC. In case of mediators, OB was found to partially mediate the relationship between PAI and PBC while it did not mediate two other direct relationships. Further, PB did not mediate any relationship at all.

The paper is expected to be useful for the academicians involved in investigating the role of SNI on PBC as a lucrative research topic.

The hiring professionals can utilize the findings of this primary research as the guidelines for formulating effective social media background checking policies.

Using SNI for different HRM practices is comparatively new but a growing practice. However, the empirical investigation covering this area is almost absent in academia. This paper as one of the very initial attempts to reveal the role of SNI on PBC can fill that severe gap to some extent and guide future research attempts. Furthermore, the HR professionals are expected to be benefitted from the empirical results in formulating and implementing an effective media policy that will help them in utilizing the SNI in an efficient and rightful manner.

This study aims to investigate the effect of changes in iron content in 70/30 copper–nickel alloy on the corrosion process.

70Copper–30Nickel-xFe-1Mn (x = 0.4,0.6,0.8,1.0 Wt.%) alloy were prepared by the high frequency induction melting furnace. The scanning electron microscope, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy were used to analyze the morphology and component of the corrosion product film.

The results show that the corrosion resistance of 70/30 copper–nickel alloy added with 1.0%Fe is the best, and the film is divided into inner dense Cu2O composite film and outer hydration loose layer; XRD showed that after adding 1.0% Fe, the content of Cu2(OH)3Cl in the corrosion product film was significantly reduced, while the content of Cu2O remained unchanged; XPS showed that nickel accumulates in the inner layer of corrosion product film; the stage growth mode of the film, the role of nickel in it and the enrichment mechanism of iron in the inner film were summarized and discussed.

The changes in the composition and structure of the corrosion product film caused by the iron content are revealed, and the mechanism of the difference in corrosion resistance is discussed.

The purpose of this paper is to present a dual-mode proximity sensor composed of inductive and capacitive sensing modes, which can help the robot distinguish different objects and obtain distance information at the same time. A systematic study of sensor response to various objects and the function of cooperation sensing is needed. Furthermore, the application in the field of robotic area needs to be discussed.

Numerical modeling of each sensing modes and simulations based on finite element analysis method has been carried out to verify the designed dual-mode sensor. A number of objects composed of different materials are used to research the cooperation perception and proximity sensing functions. In addition, the proposed sensor is used on the palm of a mechanical hand as application experiment.

The characteristics of the sensor are summarized as follows: the sensing range of inductive mode is 0-5.6 mm for detecting a copper block and the perceive range of capacitive mode is 0-5.1 mm for detecting a plastic block. The collaborative perceive tests validated that the non-ferromagnetism metals can be distinguished by inductive mode. Correspondingly, ferromagnetism metals and dielectric objects are differentiated by capacitive mode. Application experiments results reveal that both plastic bottle and steel bottle could be detected and differentiated. The experimental results are in agreement with those of simulations.

This paper provides a study of dual-mode proximity sensor in terms of design, experiments and application.

The purpose of this paper is to introduce the analysis and performance of a hybrid multiple access scheme which combines interleave division multiple access (IDMA) and code division multiple access (CDMA), referred to as IDMA/CDMA. With experimentations, the scheme can achieve good performance with simple user ends for the system.

IDMA technique is employed as the uplink transmission and CDMA technique as the downlink transmission. The performance comparison of IDMA and IDMA/CDMA downlink is studied with Monte Carlo simulations to investigate the bit error rates. For IDMA/CDMA downlink, the signals are interleaved by random interleavers, spreaded by M‐sequence and orthogonal Gold sequence, respectively, and then transmitted over an AWGN with BPSK modulation. Moreover, a channel estimation approach for IDMA based on expectation maximization (EM) algorithm is also presented.

The multi‐user detection (MUD) algorithm in uplink IDMA systems is much simpler than that used in traditional CDMA systems. It is also well known that the orthogonal spreading codes in CDMA can effectively help suppress the MAI in the synchronized environments. But for the asynchronized application, the performance of CDMA systems will degrade due to the serious multiple user interference. According to traditional IDMA and orthogonal code division multiple access/IDMA signal detection algorithms, every UE has to detect all of the signals of other users for iterative detection. The advantages of IDMA and CDMA technologies can be utilized substantially.

The proposed hybrid multiple access scheme can achieve a very simple chip‐by‐chip iterative MUD strategy at base station, and the simplified receiving operation at UE. On the other hand, this paper also evaluates channel estimation approach for IDMA based on EM algorithm.

This chapter highlights the close relationship between the wellbeing of faculty and students in higher education and the quality of teaching and learning. Improving teaching and learning is crucial for promoting the wellbeing of both faculty and students. As such, instructional leadership, an approach that focuses on enhancing teaching and learning, should be a priority for higher education leaders. However, the involvement of higher education leaders in instructional leadership is often limited. Therefore, a customized version of instructional leadership that considers the unique priorities, characteristics, and norms of this specific educational context should be implemented in higher education to prioritize the improvement of teaching and learning and, consequently, enhance the wellbeing of faculty and students.