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This study investigates the different effects of the (mis)alignment between servitization strategies (i.e. product-oriented and customer-oriented services) and inter-organizational information technology (IT) capabilities (i.e. IT reconfiguration and integration) concerning the environmental performance of servitized manufacturing firms.

Using hierarchical regression analysis, this study examines the theoretical model based on multi-respondent survey data from 1,149 senior managers of 383 manufacturers in China.

Product-oriented services have a non-significant effect on environmental performance, whereas customer-oriented services exert a significantly positive effect. The alignment between product-oriented services and IT reconfiguration, and that between customer-oriented services and IT integration, improve environmental performance. In contrast, the misalignment between product-oriented services and IT integration, and that between customer-oriented services and IT reconfiguration, hurt environmental performance.

This study elucidates the different effects of the (mis)alignment between servitization strategies and inter-organizational IT capabilities on environmental performance. It also resolves the inconsistency regarding the implications of servitization on environmental performance.

Reward-based crowdfunding, an emerging financing channel for SMEs, has attracted significant attention from scholars and practitioners. Scholars have mostly explored investors’ herding behavior in platforms to better understand investors’ decision-making mechanisms and management of funding projects. However, current evidence is inconsistent regarding herding behavior during the funding process. This study proposes prior funding performances have a nonlinear effect on subsequent funding performance and that this nonlinear relationship is conditional on competition intensity and information disclosure.

Based on objective data collected from a dominant reward-based crowdfunding platform in China, this study follows a panel ordinary least squares (OLS) model to estimate the effects of prior funding performance on the subsequent funding performance and the moderating role of environmental factors (i.e. competition intensity and information disclosure) in a given platform.

The results show prior funding performance had an inverted U-shaped effect on subsequent performance; this inverted U-shaped relationship was attenuated when the number of interactive messages was larger and competition was more intense, and it was strengthened when information updates were more frequent.

The effects of prior funding performance on subsequent performance at different stages of the fundraising process and under different platform environments remains unclear. The authors revisit the varying viewpoints in existing research and propose that the enhancement and substitution effects of prior funding performance are dominant at different funding stages. Overall, the results of this study highlight that the crowdfunding platform environment may become a boundary condition for investors' herding behavior.

Despite the potential influence of data analytics capability on servitization, the understanding of the underlying mechanisms of this influence remains unclear. This study aims to explore how data analytics capability affects servitization by examining the mediation effect of bricolage and the conditional role of innovation orientation.

This study employs the moderated mediation method to examine the proposed research model with archival data and multiple-respondent surveys from 1,206 top managers of 402 manufacturing firms in the Yangtze River Delta area in China.

Bricolage partially mediates the positive relationship between data analytics capability and servitization, and innovation orientation positively moderates this effect.

Manufacturers can leverage bricolage to materialize data analytics capability for servitization. Manufacturers should also pursue an innovation orientation to fully glean the benefits of bricolage in transforming data analytics capability into servitization.

This study opens the black box of how data analytics capability affects servitization by revealing the underlying mechanism of bricolage and the boundary condition role of innovation orientation for this mechanism. It offers valuable insights for practitioners to leverage data analytics to improve servitization through developing bricolage and cultivating a culture of innovation orientation.

Although big data analytics managerial skills (BDAMS) offer opportunities for firms to foster organizational agility, existing studies present inconclusive indications of this impact, with an overlooking of the intermediate pathways involved. This study explored how BDAMS affect organizational agility by investigating the mediation effect of data-driven organizational learning (DDOL) and the moderating roles of technological and market turbulence.

This study employed mediation and moderated mediation analyses to test the hypotheses using data collected from listed Chinese firms. Furthermore, we performed a fuzzy set qualitative comparative analysis (fsQCA) as a supplementary approach to identify the configurations that lead to organizational agility.

This study shows that DDOL partially mediates the relationship between BDAMS and organizational agility. Besides, technological and market turbulence positively moderate the effect of DDOL on organizational agility and the mediation effect of DDOL. Our additional analyses also reveal several patterns of conditions that facilitate agility.

This study offers a comprehensive exploration of the relationship between BDAMS and organizational agility by verifying the mediating effect of DDOL and moderating effects of technological and market turbulence. In addition, the fsQCA results highlighted the combinatorial effects of key factors in this study, reinforcing and refining the moderated mediation results.

In light of the lack of subjective criteria and scientific rationality in current sustainability performance assessment, the purpose of this paper is conducted to improve the sustainability performance assessment of high-tech firms by developing a hybrid approach that integrates quantitative and qualitative research methods.

This study proposed a hybrid approach that integrates word frequency analysis, cluster analysis, grey theory and the decision-making and trial evaluation laboratory (DEMATEL) method. Specifically, this study identifies useful criteria using quantitative word frequency analysis as well as qualitative literature research. Then, cluster analysis is used to divide these criteria into different categories. Subsequently, this study applies the grey theory associated with the DEMATEL method to assess the sustainability performance of high-tech firms.

The results reveal that the socio-environment is an important aspect underlying the corporate sustainability performance of high-tech firms. Therefore, high-tech firms should enhance their pollution emission control capabilities and increase investment in energy-conservation and emission-reduction technologies to drive sustainable development. In addition, increasing green product sales revenue and improving the guiding capability of green consumption are core issues that firms must address.

This study assesses the sustainability performance of high-tech firms by applying a hybrid method. This method can be used to construct a framework for scientific sustainability performance assessment and to provide a clear direction for the sustainable development of firms.

The purpose of this paper is threefold: to present internet of things (IoT)-based cyber-physical system (CPS) architecture framework to facilitate the integration of IoT and CPS; to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and to devise evaluation methods and conduct experimental evaluations on an IoT-based CPS prototype.

The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed.

The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment.

The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics.

The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

Facial recognition payment is an emerging mobile payment method that uses human biometrics for personal identification. The purpose of this study is to examine how users' salient beliefs regarding the technology–organization–environment–individual (TOE–I) dimensions affect their attitudes and how attitudes subsequently influence the intention to use facial recognition payment in offline contactless services.

This study comprehensively investigates customers' decision-making psychological mechanism of using facial recognition payment by integrating the belief–attitude–intention (B–A–I) model and the extended TOE–I framework. Data from 420 valid samples were collected through an online survey and analyzed using partial least squares structural equation modeling.

Research results indicate that convenience and perceived herd exert positive effects on trust and satisfaction. Meanwhile, familiarity has a significantly positive effect only on trust but not on satisfaction. In contrast, perceived privacy risk exhibits a negative effect on both trust and satisfaction. Trust and satisfaction positively influence the intention to use facial recognition payment. Unexpectedly, self-awareness negatively moderates the effect of satisfaction on intention to use, but its effect on the relationship between trust and intention to use is non-significant.

To the best of the authors’ knowledge, this study is one of the early studies that explicate customers' psychological mechanism in facial recognition payment in offline contactless services through an understanding of the B–A–I causal linkages with the identification of users' perceptions from a comprehensive context-specific perspective. This study enriches the literature on facial recognition payment and explores the moderating role of self-awareness in the relationship between users' attitudes and intention to use, thereby revealing a complex psychological process in the usage of offline facial recognition payment systems.

The purpose of this study is to construct a Chinese information science resource ontology and to explore a new method for semiautomatic ontology construction.

More than 8,290 articles indexed in the Chinese Social Science Citation Index (CSSCI), covering the years 2001 to 2010, were included in this study. Statistical analysis, co-occurrence analysis, and semantic similarity methods were applied to the selected articles. The ontology was built using existing construction principles and methods, as well as categories and hierarchy definitions based on CSSCI indexing fields.

Seven categories were found to be relevant for the Chinese information science resource ontology, which, in this study, consists of a three-tier architecture, 78,291 instances, and 182,109 pairs of semantic relations. These results indicate the following: further improvements are required in ontology construction methods; resource ontology is a breakthrough concept in ontology studies; the combination of semantic similarities and co-occurrence analysis can quantitatively describe relationships between concepts.

This study pioneers the resource ontology concept. It is one of the first to combine informetric methods with semantic similarity to reveal deep relationships in textual data.