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In the context of the digital age, this study aims to investigate the impact of citizens' digital participation on the scientific and democratic decision-making processes of the government. Specifically, the authors focus on the factors influencing citizens' digital participation, with a particular emphasis on their digital skills.

Exploring the influence of citizens' digital skills on their digital participation is of great practical significance for eliminating the digital divide and for promoting a life characterized by enriched digital interactions with the public. This study selected the social consciousness survey database of Chinese netizens in 2017, used ordered Probit and OLS models, and comprehensively used the instrumental variable method (IV), causal stepwise regression method and bootstrap method to empirically verify and construct a mechanism model of the influence of digital skills on citizens' digital participation.

The empirical findings indicate a noteworthy positive association between citizens' proficiency in digital skills and their active engagement in digital activities. This relationship is positively mediated by factors such as political interest and attention to social issues, underscoring their role in encouraging greater digital participation. Conversely, national identity exhibits a counteractive influence on this mechanism, potentially discouraging digital engagement. Notably, the impact of digital skill mastery on digital participation is more pronounced among non-elderly individuals and those residing in metropolitan areas, highlighting the significance of demographic characteristics in this context.

These research results can help the government and other organizations make better decisions and facilitate improvement of citizens' digital participation by promoting their mastery of digital skills.

The present study investigates the impact of supply chain disruption orientation (SCDO) on four supply chain disruption (SCD) mitigation strategies: supply chain integration (SCI), supply chain agility (SCA), supply chain visibility (SCV) and supply chain redundancy (SCR). It also examines the impact of the four mitigation strategies on SCD. The impact of the latter on business performance (BP) is also explored.

This study employs an empirical approach through survey research methodology. It analyzes data collected from 304 managers from pharmaceutical distribution companies in Jordan. Appropriate validity and reliability tests were employed for the study constructs. Path analysis using AMOS software was performed to test the study hypotheses.

SCDO was found to positively affect all SCD mitigation strategies. Furthermore, among the four mitigation strategies examined, SCV exhibited the highest significant impact in reducing SCD, followed by SCA and then SCR. However, the results revealed that SCI did not significantly impact SCD. Additionally, SCD proved to be negatively and significantly related to BP.

The present study fills a gap in the literature regarding the management of SCDs in pharmaceutical supply chains (SCs) generally and SCs of pharmaceutical distribution companies specifically. It also addresses an under-investigated area in the literature concerning the role of SCDO in promoting the adoption of SCD mitigation strategies.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

Family businesses are on the rise and facing severe sustainability challenges. The overall purpose of this thesis is to examine the moderating role of technological resources in the relationship between marketing innovation and family business sustainability.

From a post-positivist perspective, this study utilized a quantitative approach and causal research design. 204 family businesses within the Accra Metropolitan Assembly were sampled for this study. Structural Equation Modeling (SMART PLS 4) was utilized for data analysis after a closed-ended questionnaire was used to gather data.

It was evidenced that marketing innovation has a positive significant effect on family business sustainability. Technological resources have a negative significant moderating effect on the relationship between marketing innovation and family business sustainability.

The originality of this study lies in examining the moderating effect of technological resources on the relationship between marketing innovation and family business sustainability in Ghana, where this phenomenon is less explored.

This study aims to explore the role of green motive (GM) and green dynamic capabilities (GDC) in green innovation (GI) through green value co-creation (GVC). Moreover, this study investigates the moderation of top management support (TMS) to strengthen the mediation of specific constructs; GM, GDC, green value co-creation (GVC) and green innovation (GI).

In total, 337 respondents (executive level/chief executive officer (CEO)) of service organizations were approached using a convenience sampling technique to collect the data through the survey method. Of these, 294 (87% response rate) duly filled responses were used in the final data analysis. In SPSS (Statistical Package for Social Sciences) v-23, the Process Macro-Hayes was used to evaluate the study's conceptual framework empirically.

The study revealed that TMS strengthened the mediation framework of GM, GDC, GVC and GI. Moreover, all hypotheses related to direct and indirect associations of specific constructs used in the theoretical framework were statistically significant and proved.

The comprehensive framework for GI of service organizations, primarily in the context of developing countries like Pakistan, is deficient in literature. This study helps service organizations by providing a comprehensive GI model to put a central focus on the transformation of management philosophy and working approach for achieving GI in the services structure.

Green technology innovation is the organic combination of green development and innovation driven. It is also a powerful guarantee for shaping sustainable competitive advantages of manufacturing enterprises. To explore what kind of executive incentive contracts can truly stimulate green technology innovation, this study aims to distinguish the equity incentive and reputation incentive, upon their contractual elements characteristics and green governance effects, and then put forward suggestions for green technology innovation accordingly.

This study establishes an evaluation model and uses empirical methods to test. Concretely, using data from A-share listed manufacturing companies for the period from 2007 to 2020, this study compares and analyzes the impact of equity and reputation incentive on green technology innovation and explores the relationship between internal green business behavior and external green in depth.

This study finds that reputation incentives focus on long-term and non-utilitarian orientation, which can promote green technology innovation in enterprises. While equity incentives, linked to performance indicators, have a inhibitory effect on green technology innovation. Internal and external institutional factors such as energy conservation measures, the “three wastes” management system, and environmental recognition play the regulatory role in the relationship between incentive contracts and green technology innovation.

Those findings validate and expand the efficient contracting hypothesis and the rent extraction hypothesis from the perspective of green technology innovation and provide useful implications for the design of green governance systems in manufacturing enterprises.

To clarify divergent conclusions on the impact of alliances on green innovation (GI), this study aims to examine the non-linear relationships between dual alliance and GI, as well as the mediation of green knowledge reconstruction (GKR) and the moderation of alliance tie strength.

Based on the theory of knowledge-based view, a moderated intermediary model is constructed by introducing GKR and alliance tie strength. The hypotheses are validated by using hierarchical regression analysis and bootstrapping method, with questionnaire survey data collected from 316 manufacturing firms in China.

Empirical results show that both exploratory alliance and exploitative alliance have an inverted U-shaped effect on GI, in which GKR plays a mediating role in the above relationship. Moreover, alliance tie strength weakens the intermediary role of GKR in the relationship between exploratory alliance and GI, whereas it enhances the intermediary role of GKR in the relationship between exploitative alliance and GI.

Findings reveal the non-linear effects of dual alliance on GI and clarify the inconsistent conclusions by proposing the moderated intermediary effect model. Moreover, this research reveals the mechanism of dual alliance on GI through the mediation of GKR and enriches the boundary conditions by integrating the moderating role of alliance tie strength.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This research looks at the link between corporate social responsibility (CSR) and environmental performance, considering the immediate mutual interaction and the potential mediation of specific variables like green innovation and green human resource management (GHRM).

Partial least squares path modeling was used to investigate a sample of 460 respondents in multinational textile manufacturing companies in Ethiopia.

The findings of this study reveal a direct and positive relationship between CSR and environmental performance. In addition, the researchers observed an indirect effect on the relationship by using GHRM and green innovation as mediators.

The study applied a cross-sectional methodology, and experts are not sure that CSR, GHRM, and green innovation in Textile manufacturing companies provide the same results over time. Consequently, future researchers can utilize the same method of investigation to see if outcomes change or stay the same over time. Second the study was conducted in Ethiopia. As a resut, it is possible that our study results will not be generalizable to other emerging nations. We propose expanding research to include more nations with developing markets.

Executives of textile manufacturing companies can adopt the present study framework of performance in developing economies to reduce waste, pollution and air emissions, and conserve water, energy and nonrenewable resources that enhance environmental performance.

The discovery of the present research makes significant contributions to the literature on the impact of CSR on environmental performance as a pioneering study by incorporating CSR, GHRM, green innovation and environmental performance under one research model in an emerging economy context.

The manufacturing industry has recently faced many environmental issues and pressures due to increased environmental awareness. Business leaders identified that green innovation (GI) is a crucial aspect of sustainable development (SD) and can provide a competitive edge. On the other hand, boosting SD through GI is a complicated network activity involving various partners, and there is a need to transmit or share knowledge equitably and acceptably. Following the natural resource-based view (NRBV), this research presents a novel framework for investigating how green knowledge sharing (GKS) and green dynamic capabilities (GDC) affect green creativity (GC) and GI directly and through GC. Besides, the moderation of mimetic pressure (MP) was also evaluated in these targeted relations, as it is a critical element for enhancing GI in the context of SD.

Data consisted 232 respondents from Pakistani manufacturing industries, and seven substantial hypotheses were verified regarding the direct, mediating and moderating effect of targeted variables in confounding ways using partial least squares structural equation modeling (PLS-SEM).

According to the empirical findings, GKS and GDC positively correlate with GC and GI. Moreover, GKS and GDC significantly and positively impact GI both directly and indirectly. Furthermore, GC partially mediates GI, whereas MP has a significant moderating effect in these relationships.

A significant correlation among these constructs was observed, demonstrating the conceptual framework for this study. These findings can assist practitioners and academics gain a better understanding of how to manage and evaluate GI in manufacturing projects at both the project and firm levels. Therefore, policymakers and project managers can enhance GI by focusing more on GKS, GDC, MP and GC.