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The device, amplifies and sub-regionally transmits the current generated by the body temperature thermoelectric generator through a smart body temperature sensor.

The present study designs a wearable smart device regarding the relationship between temperature and emotion.

Experimental results show that the device can accurately detect changes in human body temperature under hilarious, fearful, soothing and angry emotions, so as to achieve changes in clothing colors, namely blue, red, green and brown.

Different areas of clothing produce controllable and intelligent color, so that adult emotions can be understood through changes in clothing colors, which is conducive to judging their moods and promoting social interaction.

Drawing upon socio-technical system theory, this study intends to investigate the effects of the congruence and incongruence between artificial intelligence (AI) and explorative learning on supply chain resilience as well as the moderating role of organizational inertia.

Using survey data collected from 170 Chinese manufacturing firms, we performed polynomial regression and response surface analyses to test our hypotheses.

We find that the congruence between AI and explorative learning enhances firms’ supply chain resilience, while the incongruence between these two factors impairs their supply chain resilience. In addition, compared with low–low congruence, high–high congruence between AI and explorative learning improves supply chain resilience to a greater extent. Moreover, organizational inertia attenuates the positive influence of the congruence between AI and explorative learning on supply chain resilience, while it aggravates the negative influence of the incongruence between these two factors on supply chain resilience.

Our study expands the literature on supply chain resilience by demonstrating that the congruence between a firm’s AI (i.e. technical aspect) and explorative learning (i.e. social aspect) boosts its supply chain resilience. More importantly, our study sheds new light on the role of organizational inertia in moderating the congruent effect of AI and explorative learning, thereby extending the boundary condition for socio-technical system theory in the supply chain resilience literature.

Top management and managers must highlight environmental issues and adopt green product innovation (GPI) to implement eco-friendly management in their businesses. This research aims to examine the impact of top management’s green commitment and adaptability culture (AC) on organizational green performance (OGP) mediated by GPI.

The study was conducted in the context of the textile industry of Pakistan, where a sample of 232 employees was collected for the data analysis. The study adopted a quantitative approach, and the data collected were analyzed using relevant statistical tools (SPSS 24 and Smart PLS 3.0) to address the research questions.

The present study supported positive relationships of top management green commitment (TMGC) and AC with the OGP, whereas GPI mediated the relationships.

Integrating the AC, TMGC, GPI and the organization’s green performance is a milestone as it serves as an effort to present a model promoting green management research. The study’s findings could be used in the textile sector to foster a green culture by strengthening green AC and GPI by raising environmental concerns within the workforce.

The embedding of digital technology and the fuzzy organizational boundary have changed the operation of platform innovation ecosystem (PIE). Specifically, as an important energy of PIE, the internal logic of knowledge flow needs to be reconsidered in the context of digital age, which will be helpful to select the cultivation and governance strategy of PIE.

A dual case-analysis is applied to open the “black box” of knowledge flow in the PIE from the perspective of enabled by digital technology, by taking the intellectual property (IP) operation platform as cases.

The research findings are as follow: (1) The knowledge flow mechanism of PIE is mainly demonstrated through the processes of knowledge acquisition, knowledge integration and knowledge spillover. During this process, connectivity empowerment and scenario empowerment realize the digital empowerment of the platform. (2) Connectivity empowerment provides a channel of knowledge acquisition for the digital connection between participants in PIE. In the process of knowledge integration, scenario empowerment improves the opportunities for accurate matching and collaborative innovation between knowledge supplier and demander, and enhance the value of knowledge. The dual effect of connectivity empowerment and scenario empowerment has accelerated the knowledge spillover in PIE. Particularly, connectivity empowerment expands the range of knowledge spillover, and scenario empowerment affects the generativity of the platform, resulting in the enhancement of platform’s capability to embed and expand its value network. (3) Participants have been benefitted from the PIE enabled by digital technology through three key modules (knowledge acquisition, knowledge integration and knowledge spillover), as the result of knowledge flow.

This study focuses on the knowledge flow mechanism of PIE enabled by digital technology, which enriches the PIE theory, and has enlightenments for the cultivation of digital platform ecosystem.

Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

This article aims at analysing the factors influencing the adoption of green economy practices across different sizes of firms in India.

This study is based on the World Bank Enterprise Survey 2022, covering 9,376 firms in India. The Poisson Count Regression Model has been used to analyse the factors affecting the adoption of green economy practices.

About 83 % of firms reported adopting at least one green practice in their business related to energy conservation, water management, pollution control and waste management and recycling. Research results reveal a significant association between the size of the firm and adoption of green economy practices. The impact of enterprise characteristics varies by firm size. For instance, female ownership positively affects adoption in large firms but negatively in small and medium-sized enterprises (SMEs). However, lean operations, research and development (R&D) spending and international quality certification positively influence green practices adoption for both SMEs and large firms. Perceived business obstacles show similar implications on green practices adoption by size of firms except access to finance, business licencing, tax rate and law and order affect SMEs while labour regulations, tax administration and political instability affect large firms.

This paper suggests implications for strengthening the adoption of green economy practices across firm sizes and provides opportunities for future research.

This study is based on a unique dataset derived from the World Bank Enterprise Survey 2022, which has included green economy indicators for the first time.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0918.

Asteroids have the characteristics of noncooperative, irregular gravity and complex terrain on the surface, which cause difficulties in successful landing for conventional landers. The purpose of this paper is to study the trajectory tracking problem of a multi-node flexible lander with unknown flexible coefficient and space disturbance.

To facilitate the stability analysis, this paper constructs a simplified dynamic model of the multi-node flexible lander. By introducing the nonlinear transformation, a concurrent learning-based adaptive trajectory tracking guidance law is designed to ensure tracking performance, which uses both real-time information and historical data to estimate the parameters without persistent excitation (PE) conditions. A data selection algorithm is developed to enhance the richness of historical data, which can improve the convergence rate of the parameter estimation and the guidance performance.

Finally, Lyapunov stability theory is used to prove that the unknown parameters can converge to their actual value and, meanwhile, the closed-loop system is stable. The effectiveness of the proposed algorithm is further verified through simulations.

This paper provides a new design idea for future asteroid landers, and a trajectory tracking controller based on concurrent learning and preset performance is first proposed.

The purpose of this paper is to examine the relationship between toxic workplace environments, negative workplace gossip and knowledge hiding, by exploring workplace spirituality as a moderating variable in this relationship.

This study focusses on private university lecturer in West Java, Indonesia. Data collection was carried out by distributing questionnaires to respondents offline and online via Google Forms. Data analysis was done by structural equation modeling (SEM).

The findings reveal that a toxic workplace environment and negative workplace gossip are positively related to knowledge hiding. In addition, it was found that workplace spirituality moderates the relationship between a toxic workplace environment and negative workplace gossip with knowledge hiding.

This study extends the research model and research context of knowledge hiding in private universities. This research contributes to the social exchange theory literature by proving empirical support to confirm that there is a social exchange in interpersonal relations between academics.

This study extends the research model and research context of knowledge hiding in private universities, linking it to the conservation of resources theory. This research contributes to the social exchange theory literature by proving empirical support to confirm that there is a social exchange in interpersonal relations between lecturers.

Leaders need to instill spirituality in lecturer so that they feel comfortable when working, and it indirectly reduces the effects of negative behavior such as negative gossip and a toxic environment that makes them willing to share knowledge.

To the authors’ understanding, this is the first study to examine workplace spirituality as a variable moderating the relationship between toxic workplace environment and negative workplace gossip with knowledge hiding in the college context.

The principal purposes of the research are to empirically investigate three forms of perceived overload on social media and shed light on their associations with users’ passive usage intention by contemplating the mediating influence of social network exhaustion and discontented feelings.

This study employed a cross-sectional methodology to collect statistical data (N = 679) from WeChat users in mainland China. Primitive analysis, confirmatory factor analysis and structural equation modeling were employed to test the corresponding hypotheses.

The findings reveal that three dimensions of perceived overload influence social network exhaustion positively. In addition, communication overload and system feature overload exert positive impacts on the discontented feeling. Furthermore, it is uncovered that social network exhaustion and discontented feeling are related to passive usage intention positively.

Theoretically, this paper offers a conceptual framework to explicate passive usage intention through elucidating social network exhaustion and the discontented feeling that arises from perceived overload in contemporary social media-mediated environments. Practically, the current research has certain realistic implications for WeChat users and SNS operators.

Probing what triggers people’s passive usage intention of social media has been an emerging theme in recent years, yet there is a dearth of discourse that delves into the antecedents of WeChat users’ passive usage intention. The results obtained from the study have enhanced the understanding of the adverse consequences associated with the utilization of social media in mainland China.

Polyethylene terephthalate (PET) as a fiber molding polymer is widely used in aerospace, electrical and electronic, clothing and other fields. The purpose of this study is to improve the thermal insulation performance of polyethylene terephthalate (PET), the SiO₂ aerogel/PET composites slices and fibers were prepared, and the effects of the SiO₂ aerogel on the morphology, structure, crystallization property and thermal conductivity of the SiO₂ aerogel/PET composites slices and their fibers were systematically investigated.

The mass ratio of purified terephthalic acid and ethylene glycol was selected as 1:1.5, which was premixed with Sb₂O₃ and the corresponding mass of SiO₂ aerogel, and SiO₂ aerogel/PET composites were prepared by direct esterification and in-situ polymerization. The SiO₂ aerogel/PET composite fibers were prepared by melt-spinning method.

The results showed that the SiO₂ aerogel was uniformly dispersed in the PET matrix. The thermal insulation coefficient of PET was significantly reduced by the addition of SiO₂ aerogel, and the thermal conductivity of the 1.0 Wt.% SiO₂ aerogel/PET composites was reduced by 75.74 mW/(m · K) compared to the pure PET. The thermal conductivity of the 0.8 Wt.% SiO₂ aerogel/PET composite fiber was reduced by 46.06% compared to the pure PET fiber. The crystallinity and flame-retardant coefficient of the SiO₂ aerogel/PET composite fibers showed an increasing trend with the addition of SiO₂ aerogel.

The SiO₂ aerogel/PET composite slices and their fibers have good thermal insulation properties and exhibit good potential for application in the field of thermal insulation, such as warm clothes. In today’s society where the energy crisis is becoming increasingly serious, improving the thermal insulation performance of PET to reduce energy loss will be of great significance to alleviate the energy crisis.

In this study, SiO₂ aerogel/PET composite slices and their fibers were prepared by an in situ polymerization process, which solved the problem of difficult dispersion of nanoparticles in the matrix and the thermal conductivity of PET significantly reduced.