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The purpose of this paper is to investigate the relationship between firms’ life cycle stages (mature vs growth) and green process innovation performance. In addition, this research delineates the mechanism by which the mature stage firms are more strongly associated with green process innovation performance compared to growth stage firms and recognizes technological capabilities as a mediating variable fundamental to achieve a higher level of green process innovation performance.

This research collected data from 202 publicly listed Thai manufacturing firms. Initially, it used multiple regression analysis to test the relationship between mature stage firms and green process innovation performance compared to the relationship between growth stage firms and green process innovation performance. Later, this research followed Muller et al. (2005) to test the mediating role of technological capabilities and conducted (Sobel, 1982, 1986; Preacher and Hayes, 2004) tests to further validate the mediation effect.

The hypothesized relationships were found to be significant, providing a strong support that mature stage firms have higher green process innovation performance compared with growth stage firms. Moreover, the technological capabilities more strongly mediate the relationship between mature stage firms and green process innovation performance compared to growth stage firms and green process innovation performance.

This research contributes to the existing understanding about the internal drivers of green process innovation performance by incorporating and analyzing the firms’ life cycle stages as an internal driver. This research also contributes by empirically testing the mediating role of technological capabilities on the relationship between firms’ life cycle stages and green process innovation performance.

The purpose of this paper is to examine firms’ knowledge-sourcing behavior in green technology development with respect to the home country’s market- vs nonmarket environmental policy stringency.

This paper empirically analyzes the effects of market and nonmarket environmental policy stringency on firms’ knowledge sourcing activity with patent data from OECD countries during 1991–2010, across five categories of green technologies.

When a nation establishes more stringent market environmental policies, firms likely source more international knowledge rather than domestic knowledge about green technology, up to a point. After that level, this balance shifts (inverted U-shaped curve) due to the risks associated with greater investment costs and commerciality. Nonmarket environmental policies instead should exhibit a positive, linear relationship with international relative to domestic knowledge sourcing. This study also reveals the dynamic roles of a firm’s green technological capability with market-based environmental policy stringency and a substitutive role of the capability with nonmarket-based environmental policy stringency.

This study shows the effect of market and nonmarket environmental policy stringency on firms’ knowledge sourcing. The findings provide meaningful implications for policymakers regarding the optimal levels of market and nonmarket environmental policy stringency that will enhance their countries’ green technology development.

This paper enriches the literature of environmental policy and knowledge sourcing and offers the direction of future research of how environmental policy stringency influences a firm’s knowledge sourcing for green technology development.

This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.

This study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.

The study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.

The findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

This research aims to explore the concept of green dynamic capabilities, which can facilitate the adoption of green technological innovations for the purpose of enhancing brand sustainability. Specifically, the study seeks to investigate the mediating role of green technological innovations in the relationship between green dynamic capabilities and brand sustainability.

To achieve this aim, the study employed partial least squares structural equation modeling (PLS-SEM) and surveyed 316 managers of manufacturing enterprises.

The results showed that all relationships tested were positive and significant, and green technological innovation was found to be a significant mediator in the relationship between green dynamic capabilities and brand sustainability.

By adding a mediating variable (green technological innovations), this study adds to the literature on sustainability as well as contributes to the on-going debate on how manufacturing firms can be related to environmental issues in their productions.

Green knowledge management (GKM) has become a more prominent research topic because of its ability to balance business sustainability, performance and society's well-being. The purpose of this paper is to study how GKM literature evolved before and after two major events: the introduction of sustainable development goals (SDGs) and the first conceptualization of GKM. In this paper, GKM is holistically examined following the stages of the knowledge management cycle, a framework for organizational knowledge-processing phases.

This study performed a bibliometric analysis of 1,274 papers related to GKM from 1995 until January 2024.

Over the three decades, this research outlined the intertwined relationships between core themes in the domain such as knowledge management in the context of corporate social responsibilities, sustainable development (SD), competitive advantage and so on, and popular theories. GKM evolved from an “industrial and technical view” of knowledge management to a more emerging perspective of a “social process.” Emerging themes were identified such as green innovation, information security or organizational learning sub-themes with key technologies like block-chain, big data analytics and artificial intelligence. Future research can explore themes such as green knowledge integration, green entrepreneurship, green supply chain and green knowledge integration capabilities.

This review offers practitioners a holistic picture of GKM to tackle emerging environmental concerns and increase businesses' competitive advantages. This study provides insights into the future practices of GKM, incorporating emerging technological advancement, to gain green intellectual capital and build dynamic capabilities for sustainability.

To the best of authors’ knowledge, this study is the first to provide a comprehensive picture of the GKM literature, from its earliest forms of corporate social responsibility and SD until the introduction of SDGs, and in combination with the evolution of knowledge management cycle stages.

This study investigates the impact of personal, organisational and innovation capability on technological innovation and further impacts on small and medium enterprises’ (SMEs') performance during uncertainty. Moreover, the moderator role of social sustainability orientation on the relationships of technological innovation, innovation performance and organisational resilience is also examined.

A quantitative approach using 524 SME responses and Smart PLS 4.0 are adopted in this research.

The results indicate a correlation between three types of capabilities with technological innovation and further conversion to organisational resilience. Additionally, social sustainability shows a negative moderating effect between innovation performance and organisational resilience. The research findings advanced the resources-based-view (RBV) by proposing three capability dimensions as platforms for SMEs' innovation success, which later generate resilience possibilities. Specifically highlighted in this study are the personal capabilities of managers, organisational capabilities and innovation capabilities in setting business objectives and resource allocation towards economic and sustainable goals during turbulence and uncertainty.

This study investigates the role of technological innovation and innovation on SME resilience. Notably, we deploy the social sustainability orientation as moderators towards the relationship between technological innovation, innovation performance and SMEs’ resilience. SMEs employing social sustainability orientation might negatively inhibit the translation from innovation performance to SME resilience, providing novel insights into navigating uncertainty in modern business. It has no effect on the relationship between technological innovation and its consequences.

This paper develops a contingency based model to understand how green technologies and green manufacturing performance measures evolve with the green manufacturing maturity levels of the firms.

A conceptual research model is developed by synthesizing extant literature. An illustrative case study of a paint manufacturing company is conducted, analyzing its five key green initiatives, which it has undertaken to demonstrate the research model. The primary means of data collection was interviews and document analysis.

It was observed that for all the five green initiatives, the choice of green technologies and the use of green manufacturing performance measures corroborate with the proposed research model. Further, the initial green manufacturing effort was motivated to comply with regulations, which subsequently shifted to gain strategic advantage, such as cost reduction and visibility.

The proposed model was applied only to an Indian paint manufacturing company with their five key green initiatives, which potentially limits the generalizability of the findings to other industries and/or geographies.

The findings would aid practitioners in understanding both selection of green technology and the use of green manufacturing performance measures, based on a firm's maturity stage.

This study conducts a much-needed research on the evolution of green technology alternatives and green manufacturing performance measures for firms according to the four-stage maturity model derived from the natural resourced-based view.

Despite the construction industry's significant impact on high energy use and a growing carbon footprint, technologies like Green BIM help to optimize natural resources, reduce pollution, use sustainable space and work on human comfort and health. But the trend in a holistic approach is minimal. Thus, the paper aimed to systematically investigate Green BIM research and implementation trends using a mixed-method and also show the prospects of holistic Green BIM implementation.

First, we conducted a Scientometrics analysis on the topic using the Scopus database for the time interval of (2013–present). Secondly, the Qualitative Content Review method asserted the Scientometrics analysis result. Lastly, exploratory research was done on secondary data to compare the AEC industry trend for a comprehensive view.

The merged findings confirmed the partial implementation of Green BIM and of which 43% of research focused only on energy analysis. Despite the potential of BIM and the interrelationship among green building parameters, the result showed other aspects of green building and sustainable design parameters as green material selection, sustainable site, waste management and water-use efficiency not comprised.

The authors propose a new conceptual framework for integrating green building parameters, BIM tools and green building assessment tools in a life cycle of a project that adds into the sustainability of the Architectural, Engineering and Construction sector. The study would help to provoke researchers, software developers and practitioners for further innovative effort in holistic Green BIM implementation.

This paper aims to clarify the relationship between foreign direct investment (FDI), democracy and carbon intensity. This study examines the influence of types of democracy on the relationship between inward FDI and carbon intensity. For this purpose, it uses five varieties of democracy, including a composite democracy indicator as moderating variables.

This study applies the fixed-effects panel quantile regression approach that considers unobserved heterogeneity and distributional heterogeneity using panel data from 160 countries during 1990–2020. By taking into account sudden changes in the volume of inward FDI, an event study is conducted across various sub-samples of democracy to check the robustness of the results.

The results show that FDI has a significantly negative impact on carbon intensity of the host country in the upper quantiles. In general, different types of democracy have a significant positive impact on carbon intensity across different quantiles. After considering the other factors, including industry intensity, trade openness, green technology, fossil fuel dependency and International Environmental Agreements, there is evidence that all types of democracy moderate the relationship between FDI and carbon intensity, thereby supporting the halo effect hypothesis. In addition, the interaction effects have a significant negative impact on carbon intensity of low- and high-carbon-intensive countries.

This paper offers several contributions to the literature on the effect of FDI and democracy on carbon intensity. This study overcomes the limitations related to the conceptualization and measurement of democracy found in the literature. While prior research has predominately concentrated on how democracy promotes the selection of FDI host-country locations, this study seeks to answer the question of whether democracy type has any effect on inward FDI, thus contributing to improving carbon intensity. Furthermore, this paper analyses the interaction effect on carbon intensity in different countries with different carbon intensity levels separately.

The problem of evaluating potential suppliers has always been based on finding an optimal tradeoff between supplier’s performance consistently meeting firms’ needs and acceptable cost. The purpose of this paper is to propose a hybrid multi-criteria decision framework to quantify this qualitative judgment and reduce ambiguity in selection of suppliers in the era of Industry 4.0.

A hybrid intuitionistic fuzzy entropy weight-based multi-criteria decision model with TOPSIS is proposed. The authors make use of the intuitionistic fuzzy weighted approach operator for aggregating individual decision maker’s opinions regarding each alternative over every criterion. Additionally, the authors employ the concept of Shannon’s entropy to calculate the criteria weights.

Results obtained on the basis of the proposed hybrid methodology are analyzed against two more cases wherein the authors try to showcase the relevance of using IFS and entropy-based decision framework and find out the uniqueness of the proposed framework in supplier selection process.

The proposed model is apposite to solve management problem of supplier selection in two ways: aggregating individual decision maker’s opinion for each of the predefined criteria along with individual decision maker’s importance and ranking the suppliers based on both positive and negative ideal solutions using TOPSIS.

A robust framework incorporates not only suppliers’ performance but also provides weightage to key decision makers. Especially in the context of MCDMs wherein both qualitative and quantitative data is evaluated simultaneously, the proposed framework is unique in its practical implementation of reducing ambiguity in the supplier selection process.