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This research endeavors to conduct a thorough and holistic analysis of the foundational elements that empower the cultivation of dynamic capabilities in micro, small and medium-sized enterprises (MSMEs). The purpose of this study is to determine whether these capabilities have a noticeable impact on the sustainable performance of these enterprises. The study aims to support future research efforts in understanding this phenomenon by filling this knowledge gap and presenting a conceptual framework, thereby enhancing the scholarly discourse in this field.

The study consists of a systematic review of 126 articles meticulously chosen through a series of screening stages employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. This examination is conducted within the organized framework of antecedents, decisions and outcomes-theory, context and methods (ADO-TCM), ensuring a structured and comprehensive analysis.

The study uncovers significant insights, identifying four key antecedents: resource base, organizational learning, managerial expertise and external environment management. These factors are instrumental in fostering dynamic capabilities within the enterprise, leading to sustainable entrepreneurial success and a competitive advantage over rivals.

By comprehending the mechanisms by which dynamic capabilities are established within the enterprise, this study provides a valuable resource for entrepreneurs, professionals and managers, offering them practical insights to leverage.

This systematic literature review is the initial attempt to explain how dynamic capabilities can be used to enhance and accomplish sustainable performance in the context of MSMEs.

This study aims to design a small-size conformable flexible micro-electro-mechanical system (MEMS) vector hydrophone to meet the miniaturization requirements of unmanned underwater vehicle.

The cilia receive the acoustic signal to oscillate to cause changes in the stress on the beam, which in turn causes changes in the piezoresistive resistance on the beam, and changes in the resistance cause changes in the output voltage.

The results show that the flexible hydrophone in the paper has a sensitivity of −182 dB@1 kHz (re 1V/µPa) at 1 Pa sound pressure, can detect low-frequency hydroacoustic signals from 20 to 550 Hz and has good spatial directivity, and the flexible substrate permits the hydrophone to realize bending deformation, which can be well attached to the surface of the object.

In this study, a finite element simulation model of the hydrophone microstructure is constructed and its performance is verified by simulation. The success rate of the proposed MEMS transfer process is as high as 94%, and the prepared piezoresistors exhibit excellent resistance characteristics and high consistency. These results provide innovative ideas to enhance the performance and stability and achieve miniaturization of hydrophones.

This study aimed to verify the impact of e-commerce live streaming interactivity on consumer engagement behavior. Specifically, the multiple dimensions of interactivity and tie strength together form a high-level consumer engagement behavior.

Data collection was carried out in the form of a questionnaire survey. Data from 416 respondents were analyzed by structural, followed by further test by fsQCA method.

Perceived controllability, perceived responsiveness and perceived mutuality positively influence tie strength, and tie strength promotes consumer engagement behavior. Moreover, we found a configuration effect between interactivity and tie strength and revealed four configurations that can affect high-level engagement behavior.

First, the SEM results show that the three dimensions of perceived interactivity positively impact tie strength: perceived controllability, perceived responsiveness, and perceived mutuality. And perceived personalization has no positive impact on tie strength. Second, the relevant results show that tie strength positively impacts consumer engagement behavior. Third, we find that the relationship between perceived interactivity and consumer engagement behavior may not be asymmetric, so the alternative combination of causal conditions may produce the same results. The fsQCA results revealed four configurations that can affect the level of consumer engagement behavior. And tie strength is the core condition.

This study provides specific solutions for e-retailers and live streaming platforms to promote consumers' participation in engagement behavior in e-commerce live streaming.

This study transforms the linear impact of interactivity on consumer engagement behavior into a configuration effect for the first time, and enriches the live streaming commerce and consumer engagement behavior literature.

This study aims to explore the impact mechanism of social support on individual health knowledge creation among users in online patient communities, guide and promote the creation of health knowledge and provide insights into managing online patient communities.

A theoretical model was constructed by integrating social impact and social support theories. Data were collected through questionnaires, and 750 valid responses were analysed using a structural equation model.

This study found the following. (1) Social support influences individual health knowledge creation through the mediating effects of creative self-efficacy and positive emotions. (2) The general rule of the strength of the influencing factors on individual health knowledge creation is that creative self-efficacy > positive emotions. (3) The general pattern of the mediating effect of attitude factors between social support and health knowledge creation is that creative self-efficacy > positive emotions. (4) The key path for social support to influence individual health knowledge creation is “social support → creative self-efficacy → health knowledge creation”. (5) The dimensions of social support in online patient communities can be divided into information, emotional, respect and network support. Individual health knowledge creation can be divided into health knowledge externalisation, combination, socialisation and internalisation.

This study expands the application scope of social influence theory and opens up the “black box” of the impact of social support on individual health knowledge creation behaviour. Simultaneously, the dimensions of social support, individual health knowledge creation and the mediating role between social support and health knowledge creation are discussed.

This study aims to use corporate social responsibility (CSR) reporting focused on poverty alleviation in China as a case to demonstrate a unique interplay between the state and private enterprises. It illustrates how CSR reporting has influenced both the mechanisms and outcomes of their interactive relationship, contributing to the construction of symbolic power.

Drawing on Bourdieu’s theory of symbolic power, this study explores how symbolic power has been constructed and reinforced between the state and private enterprises. It highlights the unique role of CSR reporting in facilitating an alignment between private enterprises objectives and state goals, ultimately reinforcing symbolic and social order. The empirical materials examined are the CSR reports prepared by the top 20 private enterprises in China from 2017 to 2022.

Major private business enterprises in China actively engage with the state’s objectives on poverty alleviation as reflected through their CSR reporting practices. This engagement is evidenced by shifts in keywords, dominant language and reporting structure, which closely align with the state’s stance on the issue. As a result, these enterprises receive heightened public recognition, which in turn helps reinforce the symbolic power and its influence on corporate behaviour.

This paper contributes to the CSR accounting literature by revealing a strategic role of CSR reporting that extends beyond conventional compliance levels commonly observed in Western liberal democratic societies. It serves as a function that facilitates interaction between the state and private enterprises in a symbolic power relationship, where both parties mutually benefit from the alignment of interests in poverty alleviation and social positioning.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

This study aims to develop a chain-mediated model to examine how streamer and product characteristics influence consumer behavior inertia (CBI) based on an extended cognitive-affective-conative (CAC) perspective.

This study used an online survey concerning the livestreaming activities of 250 experienced shoppers to measure the proposed model.

Streamer (product) attractiveness mediates the relationship between streamer (product) characteristics and shopping experience memory. Streamer (product) attractiveness and shopping experience memory have a chain mediating effect between the streamer (product) characteristics and CBI.

Theoretically, the study demonstrates the critical role of attractiveness and shopping experience memory in the formation of consumer inertia and complements current explanations of consumer continuance of buying through livestreaming. From a managerial standpoint, the findings provide guidelines for enterprises carrying out livestreaming business on how to improve inertia to realize a stable profit source.

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

The main goal of this paper is to present a synthetic multiple criteria group decision-making (MCGDM) methodology for assessing the enterprise digital maturity with linear Diophantine fuzzy (LDF) setting.

This paper utilizes the presented LDF generalized Dombi operator to aggregate assessment information of experts. The developed combined weight model through merging the rank sum (RS) model and symmetry point of criterion (SPC) method is used to ascertain the comprehensive importance of criterion. The evaluation based on distance from average solution (EDAS) approach based upon regret theory (RT) is presented to achieve the sorting of candidate enterprises.

Firstly, the proposed method has strong stability. Secondly, the proposed method takes into consideration the psychological behavior of experts during the decision-making process which further enhances the rationality of the decision results. Finally, the proposed method integrates expert and criterion weight determination models which provides a practical evaluation framework for assessing the digital maturity of enterprises. The research outcomes confirm that the proposed approach fails to resolve the decision problems with unknown weight information flexibly, but also reflect the psychological behavior of expert in decision process. The presented weight approach also provides a rational algorithm to ascertain the weight more accurate.

A composite LDF group decision-making approach is presented by aggregating the proposed generalized Dombi operator, combined weight model and the EDAS model, which make the outcome more reasonable. Sensitivity analysis and comparison study are conducted to reflect the superiority of the proposed approach.