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The purpose of this paper is to achieve fault reconstruction for reaction wheels in spacecraft attitude control systems (ACSs) subject to space disturbance torques.

Considering the influence of rotating reaction wheels on spacecraft attitude dynamics, a novel non-linear learning observer is suggested to robustly reconstruct the loss of reaction wheel effectiveness faults, and its stability is proven using Lyapunov’s indirect method. Further, an extension of the proposed approach to bias faults reconstruction for reaction wheels in spacecraft ACSs is performed.

The numerical example and simulation demonstrate the effectiveness of the proposed fault-reconstructing methods.

This paper includes implications for the development of reliability and survivability of on-orbit spacecrafts.

This paper proposes a novel non-linear learning observer-based reaction wheels fault reconstruction for spacecraft ACSs.

The purpose of this paper is to accomplish robust actuator fault isolation and identification for microsatellite attitude control systems (ACSs) subject to a series of space disturbance torques and gyro drifts.

For the satellite attitude dynamics with Lipschitz constraint, a multi-objective nonlinear unknown input observer (NUIO) is explored to accomplish robust actuator fault isolation based on a synthesis of H_inf techniques and regional pole assignment technique. Subsequently, a novel disturbance-decoupling learning observer (D²LO) is proposed to identify the isolated actuator fault accurately. Additionally, the design of the NUIO and the D²LO are reformulated into convex optimization problems involving linear matrix inequalities (LMIs), which can be readily solved using standard LMI tools.

The simulation studies on a microsatellite example are performed to prove the effectiveness and applicability of the proposed robust actuator fault isolation and identification methodologies.

This research includes implications for the enhancement of reliability and safety of on-orbit microsatellites.

This study proposes novel NUIO-based robust fault isolation and D²LO-based robust fault identification methodologies for spacecraft ACSs subject to a series of space disturbance torques and gyro drifts.

The COVID-19 pandemic has resulted in a brand-new phenomenon in customer consumption patterns. This resulted from heightened health awareness brought on by the COVID-19 epidemic. There is a dearth of appropriate health psychology perspectives in the existing study examining the effect of COVID-19 on consumers’ use of crowdsourced logistics (CL) platforms. In order to provide unique and thorough insights into how consumer health concerns can affect consumers’ subjective views and their decisions to use CL, this study combines the health belief model and the technology acceptance model.

Five hundred valid responses from an online survey that was created and administered in Singapore were analysed using structural equation modelling.

The findings show that all of the suggested constructs have a favourable influence on consumers’ intentions to use CL. The suggested model also demonstrates high explanatory power, with perceived usefulness serving as the primary driver, followed by perceived ease of use and self-efficacy.

The study advances previous academic research on CL and offers guidance to CL companies and lawmakers for promoting sustainable and secured last-mile delivery.

Omni-channel shopping affords consumers a variety of delivery options to receive products based on their preferred times and locations. By considering consumers' contributions (physical, social and attentive efforts) in co-creating delivery services, this study investigates their preferences for parcel delivery.

A scenario-based questionnaire survey is conducted for data collection in Singapore (n = 483). Furthermore, a multinomial logistic regression is performed to assess consumers' choice mode of delivery among five alternatives, that is attended home delivery, unattended home delivery, automated self-collection locker, attended pickup point and click-and-collect.

Compared to attended home delivery, consumers who choose the alternatives are found to be more willing to contribute physical effort but less interested in responding attentively to informational updates. Efforts required for social interactions discourage consumers from choosing attended deliveries, prompting unattended alternatives (e.g. home delivery and self-collection) as more attractive choices. Additionally, socio-demographic factors and product value also influence consumers' preferences.

This study contributes to the literature by integrating the theoretical concept of consumer logistics into omni-channel studies, providing a new approach to examining consumers' channel behaviour. With detailed profiling that links product value and consumers' socio-demographics to their choice mode of delivery, the authors create practical insight into the optimal design of omni-channel distribution systems that best harness consumers' voluntary contributions.

Logistics at work is rapidly changing. The changing trend is especially prominent when considering the active involvement of individuals that perform diverse forms of formal/informal “logistics work” (e.g. crowd logistics and self-collection). Thus, by conducting a synthesised review (n = 55), this study aims to provide a typology of individuals' logistics work.

The total social organisation of labour is used as a guiding framework. A deductive literature analysis is performed based on the identified journal articles.

The review findings reveal three major contexts where individuals perform logistics work: formal organisation, social community and private household, with a decreased level of formality. Under each context, individuals may be engaged in paid or unpaid activities, creating six forms of logistics work, termed as paid/voluntary professional logistics, incentivised/friendly social logistics and rewarded/free consumer logistics. Furthermore, an actor–sphere–resource–value conceptualisation of individual logistics is proposed, focussing on the chains of actors, work settings, resource input and value outcome.

The results provide a theoretical foundation for further research in individual- or consumer-centrism in logistics. Two research directions and seven research questions are presented for future investigation.

Previous research has examined the effects of discrete affects on voice; however, the role of trait and state affects in voice literature has received little attention. This study aims to address this important issue from a conservation of resources perspective, by exploring the influence of daily positive affect and emotional resistance to change on the voice of employees and their resulting work outcomes.

The study collected data about 285 daily episodes from 57 employees over five consecutive days, using an experience sampling method (ESM) through mobile surveys. The study found that emotional resistance to change was negatively related to employee voice and in-role performance.

Voice mediated the negative relationship between emotional resistance to change and in-role performance. The study also found that daily positive affect buffered the negative effects of emotional resistance to change on voice.

These findings extend the research concerning affect and voice; the study provides integrative insight into how affect dynamically influences organizations.

The purpose of this paper is to select the optimal feature parameters to further improve the identification accuracy of cashmere and wool.

To increase the accuracy, the authors put forward a method selecting optimal parameters based on the fusion of morphological feature and texture feature. The first step is to acquire the fiber diameter measured by the central axis algorithm. The second step is to acquire the optimal texture feature parameters. This step is mainly achieved by using the variance of secondary statistics of these two texture features to get four statistics and then finding the impact factors of gray level co-occurrence matrix relying on the relationship between the secondary statistic values and the pixel pitch. Finally, the five-dimensional feature vectors extracted from the sample image are fed into the fisher classifier.

The improvement of identification accuracy can be achieved by determining the optimal feature parameters and fusing two texture features. The average identification accuracy is 96.713% in this paper, which is very helpful to improve the efficiency of detector in the textile industry.

In this paper, a novel identification method which extracts the optimal feature parameter is proposed.

This study investigated the differential effects of empowering leadership and directive leadership in projects. Moreover, how the complex interplay between empowering and directive leadership styles influences both leader–member exchange and project performance was also explored.

Polynomial regression analysis and response surface modeling were applied to analyze 161 matched data collected from project members and managers worked in different projects located in China.

Four leadership styles were identified, i.e. ambidextrous, delegating, directive and laissez-faire styles. These may be combined with empowering and directive leadership. With regard to (in)congruence, leader–member exchange and project performance improved with ambidextrous style as a form of high–high congruence between empowering and directive leadership compared with laissez-faire style (i.e. low–low congruence). Results were better when a delegating style was combined with empowering leadership at a high level compared with the combination of directive style as directive leadership at a high level. Leader–member exchange was identified to exert a mediating role of the (in)congruence on project performance.

This study confirmed the contingent viewpoint of leadership by identifying distinct leadership styles applied in projects. Furthermore, the co-existence of empowering leadership and directive leadership was examined, and the underlying mechanism between the (in)congruence of empowering and directive leadership and project performance was identified.

As an application of self-service technology, automated parcel station (APS) is emerging as a logistics innovation to address the inefficiency and delivery failure in conventional home delivery. However, the long-term viability of APS depends on the consumers’ acceptance of such concept. In response, the purpose of this paper is to conduct a behavioural study on consumers’ adoption of self-collection service via APS.

By synthesising theoretical insights from the innovation diffusion literature and attitude theories, a conceptual model is developed and empirically validated. Perceived characteristics of APS are present to directly influence the consumers’ adoption intention, or indirectly through attitude. A total of 170 valid responses are collected from a survey conducted in Singapore and the data are analysed using structural equation modelling.

Consumers’ favourable attitude and perceived relative advantage of APS directly lead to stronger adoption intention. On the contrary, consumers’ perceptions on compatibility and trialability and on complexity indirectly influence their adoption intention via attitude, in a positive and in a negative way, respectively. Additionally, attitude is found to be the most influential factor contributing to consumers’ adoption intention.

The scope of this paper is limited to e-consumers’ initial adoption decision. Future research should examine the consumers’ adoption behaviour further down the innovation adoption process, such as continuance and commitment.

This research conceptualises and validates the consumers’ adoption behaviour of APS from a synthesised view of innovation diffusion and attitude theories, theoretically and empirically contributing to the field of study on logistics innovations from the consumers’ perspective.

Service conveniences (SCs) play a deterministic role in motivating consumers’ participation in self-collection (via attended pickup points or unattended automated locker systems). Accordingly, the SERVCON model provides a multi-dimensional conceptualisation of SCs, whereas the Kano model explains consumers’ satisfaction formation in response to multi-dimensional service attributes. Anchored on synthesised insights of both models, the purpose of this paper is twofold: first, to qualitatively apply the SC concept to develop specific service attributes of self-collection; and second, to quantitatively examine these attributes in relation to consumers’ satisfaction formation.

A quantitative Kano model is adopted for survey questionnaire design and data analysis, and 500 valid responses are obtained from an online panel of respondents in Singapore.

SCs are decomposed into 11 service attributes reflecting access, benefit, transaction and post-benefit conveniences of self-collection services. Distinctive patterns of satisfaction formation are revealed in response to specific service attributes; for example, consumers are most responsive to improvement in transaction convenience. Furthermore, as service performance level increases, benefits of spatial accessibility diminish, whereas those of temporal accessibility increase.

This study reveals key service attributes influencing the self-collection services’ convenience and impact on consumers’ satisfaction. Guidelines are presented for designing an optimal resource allocation strategy for logistics service providers to promote self-collection services.

This study synthesises diverse logistics literature on self-collection services under the central theme of SCs, thus enriching the conceptual development of SCs with a decomposed framework of logistics service attributes.