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This paper aimed to explore the presence of altmetric data across the sub-categories of the medical science discipline and also explore whether the openness of articles results in (dis)advantage for altmetrics mentions.

The research implies data carpentry methods for gathering bibliographic data related to narrow fields of medical science discipline from the Scopus database with at least one Indian author affiliation during 2012–2021. The corresponding data were also collected from three different sources: Altmetric.com, Mendeley.com and Unpaywall.org, using OpenRefine and REST/API calls. Further, the authors observed open access altmetric advantages (OAAA) and categorical OAAA (COAAA) across seven altmetric platforms for all articles as well as discipline-wise.

The result shows that the overall coverage of altmetric events is still low, but it shows an increasing trend from the past. Mendeley has the largest coverage; almost 97.12% of publications are covered. The health policy discipline has extensive coverage across altmetric platforms (nearly 57.40% of publications in altmetrics and 99.23% in Mendeley), whereas the drug guides has the lowest (almost 0.92% in Altmetrics and 77.05% in Mendeley). Moreover, the OA articles have been highly covered in altmetrics than those of non-OA articles, and bronze OA articles covered mostly compared to others. News registered with the significant OA altmetric advantages across disciplines. Categorically, bronze and hybrid OA have the largest altmetric advantages.

This research is a unique attempt to apply OAAA and COAAA to explore OA altmetric advantages of narrow subject categories of medical science disciplines.

Prior research seldom explores the different structures of marketing presence in the top management team (MPTMT) and their impact on new product performance. In this paper, we distinguish among three structures of MPTMT: (1) a dedicated MPTMT; (2) a joint marketing and sales MPTMT; and (3) a joint marketing and other operations MPTMT. We then examine how these three structures of MPTMT are related to cross-functional integration in NPD and, subsequently, new product performance.

Path analysis is used to test the model using data collected from 139 U.S. manufacturing firms. We conducted two rounds of survey data collection (with a one-year gap) to assess the potential effect of common method variance.

The results show that, compared with no MPTMT, all MPTMT structures positively affect cross-functional integration in NPD, which, in turn, enhances new product performance. However, joint MPTMT structures have a greater impact than a dedicated MPTMT. Our moderation analysis also reveals that as TMT heterogeneity increases, the effect of dedicated MPTMT diminishes, but the effects of the other two joint structures remain positive and stable.

The model could include alternative mediating organizational processes and performance outcomes.

The findings provide managers with insight on how to configure and leverage marketing influence in the upper echelons in both SMEs and large firms.

The findings of this study highlight the importance of delineating MPTMT structures, understanding how they create value, and specifying their boundary conditions.

This study aims to investigate the intention to use blockchain technology (BT) in the context of supply chain (SC) operations through an integrated technology adoption framework using two well-known models, the unified theory of acceptance and use of technology (UTAUT) and the technology acceptance model (TAM). Moreover, the study looked at the direct effect of TAM and UTAUT elements on attitude toward BT, as well as the role of attitude toward BT as a mediator between TAM and UTAUT elements and intention to use BT.

The study used a quantitative research method, and a structured questionnaire was used to gather primary data. The final sample, drawn using a convenience sampling that consisted of 273 managers from the Jordanian manufacturing sector. Structural equation modeling statistical method was conducted using the Smart PLS program to test hypotheses in the proposed study framework.

The study has provided intriguing results. It found that two UTAUT elements, namely performance expectancy and social influence and one TAM element, namely perceived usefulness, have a significant impact on the attitude toward BT. Besides that, the study found that attitude toward BT significantly mediated the relationship between UTAUT-TAM elements and intention to use BT. The findings revealed that three elements namely performance expectancy, social influence and perceived usefulness have statistical significance on intention to use BT through the mediation of attitude. Finally, there is a direct significant positive relationship between the attitude toward BT and intention to use it.

The study helps decision-makers, South Carolina practitioners and academics recognize the fundamental factors that increase manufacturing firms’ intentions to use blockchain in their SCs. This gives decision-makers a better understanding of why users accept or reject BT, as well as how to improve user acceptability through technological design. Future studies should seek for a bigger sample size and use random sampling techniques. Furthermore, the study should be replicated in other industries or developing countries to validate the findings.

There is a scarcity of studies identifying the factors that increase blockchain adoption intention in SCM and developing countries. This study differs in that it examines BT intention to use in the context of SC using an integrated technology adoption framework that uses two well-known models, UTAUT and TAM, whereas other studies typically use only one model/theory. Moreover, given the importance of attitude in behavior, this study also investigated the effect of TAM-UTAUT elements on attitude toward BT, as well as the role of attitude toward BT as a mediator between TAM and UTAUT elements and intention to use BT.

This study is designed to examine the dynamic interrelationships between four cryptocurrencies (Bitcoin, Ethereum, Dogecoin and Cardano) and the Indian equity market. Additionally, the study seeks to investigate the potential safe haven, hedge and diversification uses of these digital currencies within the Indian equity market.

This study employs the wavelet approach to examine the time-varying volatility of the studied assets and the lead-lag relationship between stocks and cryptocurrencies. The authors execute the entire analysis using daily data from 1st October 2017 to 30th September 2023.

The result of the study shows that financial distress due to the pandemic and the Russian invasion of Ukraine have a negative effect on the Indian equities and cryptocurrency markets, escalating their price volatility. Also, the connectedness between the returns of stock and digital currency exhibits a strong positive relationship during periods of financial distress. Additionally, cryptocurrencies serve as a tool of diversification or hedging in the Indian equities markets during normal financial circumstances, but they do not serve as a diversifier or safe haven during periods of financial turmoil.

This study contributes to understanding the relationship between the Indian equity market and four cryptocurrencies using wavelet techniques in the time and frequency domains, considering both normal and crisis times. This can offer valuable insights into the potential of cryptocurrencies inside the Indian equities markets, mainly with respect to varying financial conditions and investment horizons.

Amidst the growing awareness regarding the social accountability of corporates, the study has attempted to investigate how firm characteristics like size and performance influence corporate social responsibility (CSR) activities in India.

236 Indian firms listed on the National Stock Exchange (Nifty 500 index) have been selected for the empirical analysis. The independent variable firm size has been defined through total assets, operation scale and resource access. Another important factor, firm's performance, is also considered as the independent variable. CSR, the dependent variable, has been measured using Bloomberg's Environmental, Social and Governance (ESG) disclosure scores.

Findings of the dynamic panel data analysis have revealed an inversed U-shape relationship between companies' size and CSR, i.e. CSR participation is positively related with small-sized firms, but as the firms become larger in size, their relationship with CSR becomes negative. A negative relationship has also been found between firm performance and CSR, while the age of the firm exhibits a positive association with CSR participation.

Poor performance of the larger firms suggests that government regulatory bodies need to take strict steps to enhance supervision. Clear regulations are required to be framed and enforced upon large companies to promote consistent participation in CSR. The present study has endeavoured to offer a distinct viewpoint by considering firm size and CSR to be related in a non-linear manner and has brought forward relevant information from the perspective of an emerging economy like India.

This study identifies three main CSR motivations (i.e. strategic benefits, altruism and greenwashing) and explores the relationship between CSR motivations and environmental collaboration by considering the mediating role of environmental commitment and the moderating role of team autonomy.

The data collected from 336 respondents in the construction industry, structural equation modeling and bootstrapping were used to test hypotheses.

The findings show that altruistic CSR enhances environmental collaboration through enhancing environmental commitment, whereas greenwashing CSR damages environmental collaboration through reducing environmental commitment. Although there is no direct association between strategic CSR and environmental collaboration, environmental commitment mediates the effects of strategic CSR on environmental collaboration. Moreover, the positive effect of strategic CSR and altruistic CSR on environment commitment is stronger when team autonomy is stronger, whereas the negative effect of greenwashing CSR on environment commitment is weaker when team autonomy is stronger.

The findings contribute to the understanding of how CSR motivations can act as catalysts for collaborative efforts in addressing environmental issues within construction projects and offer theoretical understanding of team autonomy by illustrating its role in shaping organizational responses to CSR motivations. The findings can provide insights into why and how participating teams can collaborate better on environmental management, enriching the knowledge of environmental management practices in construction projects.

Big data capabilities have the potential to completely transform conventional methods of doing business. Nevertheless, the role of big data capabilities in fostering green marketing capabilities and improving green competitive advantage is still not fully understood. To add new knowledge, this paper aims to propose a moderated mediation model to strengthen green competitive advantage in a big data environment. The model introduces both the mediating role of green marketing capabilities and the moderating role of big data capabilities. We developed and empirically tested a moderated mediation model.

In this study, we have adopted a survey-based methodology. The study collected data from 337 managers and empirically analyzed it to test the theoretical model of moderated mediation. We employed structural equation modeling for empirical analysis.

The findings revealed that organizational learning improves green marketing capabilities, whereas the relationship between organizational learning and green competitive advantage is insignificant. The mediating role of green marketing capabilities in the relationship between organizational learning and green competitive advantage was statistically significant, indicating that green marketing capabilities serve as a bridge between organizational learning and green competitive advantage. Big data capabilities moderate the relationship between organizational learning and green marketing capabilities. The moderated mediation was also significant, highlighting that big data capabilities further strengthen the indirect effects of organizational learning on green competitive advantage via green marketing capabilities.

This paper delivers theoretical and practical understandings of the importance of organizational learning and big data capabilities. Similarly, it extends current knowledge and provides key insights for managerial decision-making.

This study aims to investigate the level of empowerment of rural women organic farmers through the Total Observed Score of a Statement-Revised scale (TOSS-R).

In doing so, exploratory factor analysis is used to investigate the factorial structure of the 8-dimensional TOSS scale. Further, first and second-order confirmatory factor analysis is used to confirm the construct reliability and model adequacy of TOSS-R. The data has been collected from 314 women organic farmers from four selected districts (Nayagarh, Khurda, Boudh, and Ganjam) of Odisha based on 2022 records from the Directorate of Horticulture.

The results showed that the TOSS-R is showing better model adequacy compared (CMIN/df = 2.031, RMSEA = 0.073, SRMR = 0.064) to the earlier TOSS scale (CMIN/df = 2.697, RMSEA = 0.840, SRMR = 0.096). Further in the analysis of the overall empowerment, the TOSS-R scale determined that 49.60% of women are highly empowered, 44.58% are moderately, and 5.73% are less empowered.

The study emphasizes that the policymakers should establish a local capacity to promote gender equity in land titling such that women irrigators will be officially labelled as “farmers”, thereby bringing them under government scheme that is exclusively granted to women farmers.

The study’s novelty lies in a more comprehensive model of determining the empowerment of women organic farmers which has the capability to determine the constraints of the women failing to be empowered in the farming sector.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2023-0693

Blockchain technology has brought about significant transformation among organizations worldwide. This study aimed to explore the effects of organizational and technological factors on blockchain technology adoption (BTA) and financial performance (FP) in Pakistan.

This is a co-relational study which used the cross-sectional data. We gathered the data from the managers of Pakistan’s small and medium-sized enterprises (SMEs), which functioned their industries with blockchain technology. We applied convenience sampling to identify the respondents. Finally, we based this study’s findings on 274 valid cases.

We used structural equation modeling (SEM) in this study, to exert a positive and significant impact on organizational factors such as organizational innovativeness (OI), organizational learning capability (OLC), top management support (TMS) and organizational work climate (OWC) on BTA. In addition, the technological factors, such as complexity (CTY), technology readiness (TR), compatibility (CBTY) and technology capability (TC), have a positive and significant effect on BTA. Finally, this study’s findings show that BTA positively and significantly impacts FP.

This study’s findings will help policymakers and planners to design policies to adopt other blockchain technologies to improve SMEs’ operations. Moreover, this study’s findings will inspire policymakers and planners to actively seek new ideas, knowledge and skills through acquiring new knowledge to assist with their IT-related decisions.

This study empirically confirms the role of organizational and technology factors toward BTA and FP among Pakistan's SME managers.

The purpose of this paper is to investigate the effect of the replacement of natural coarse aggregate (NCA) with different percentages of recycled coarse aggregate (RCA) on properties of low calcium fly ash (FA)-based geopolymer concrete (GPC) cured at oven temperature. Further, this paper aims to study the effect of partial replacement of FA by ground granulated blast slag (GGBS) in GPC made with both NCA and RCA cured under ambient temperature curing.

M25 grade of ordinary Portland cement (OPC) concrete was designed according to IS: 10262-2019 with 100% NCA as control concrete. Since no standard guidelines are available in the literature for GPC, the same mix proportion was adopted for the GPC by replacing the OPC with 100% FA and W/C ratio by alkalinity/binder ratio. All FA-based GPC mixes were prepared with 12 M of sodium hydroxide (NaOH) and an alkalinity ratio, i.e. sodium hydroxide to sodium silicate (NaOH:Na₂SiO₃) of 1:1.5, subjected to 90^°C temperature for 48 h of curing. The NCA were replaced with 50% and 100% RCA in both OPC and GPC mixes. Further, FA was partially replaced with 15% GGBS in GPC made with the above percentages of NCA and RCA, and they were given ambient temperature curing with the same molarity of NaOH and alkalinity ratio.

The workability, compressive strength, split tensile strength, flexural strength, water absorption, density, volume of voids and rebound hammer value of all the mixes were studied. Further, the relationship between compressive strength and other mechanical properties of GPC mixes were established and compared with the well-established relationships available for conventional concrete. From the experimental results, it is found that the compressive strength of GPC under ambient curing condition at 28 days with 100% NCA, 50% RCA and 100% RCA were, respectively, 14.8%, 12.85% and 17.76% higher than those of OPC concrete. Further, it is found that 85% FA and 15% GGBS-based GPC with RCA under ambient curing shown superior performance than OPC concrete and FA-based GPC cured under oven curing.

The scope of the present paper is limited to replace the FA by 15% GGBS. Further, only 50% and 100% RCA are used in place of natural aggregate. However, in future study, the replacement of FA by different amounts of GGBS (20%, 25%, 30% and 35%) may be tried to decide the optimum utilisation of GGBS so that the applications of GPC can be widely used in cast in situ applications, i.e. under ambient curing condition. Further, in the present study, the natural aggregate is replaced with only 50% and 100% RCA in GPC. However, further investigations may be carried out by considering different percentages between 50 and 100 with the optimum compositions of FA and GGBS to enhance the use of RCA in GPC applications. The present study is further limited to only the mechanical properties and a few other properties of GPC. For wider use of GPC under ambient curing conditions, the structural performance of GPC needs to be understood. Therefore, the structural performance of GPC subjected to different loadings under ambient curing with RCA to be investigated in future study.

The replacement percentage of natural aggregate by RCA may be further enhanced to 50% in GPC under ambient curing condition without compromising on the mechanical properties of concrete. This may be a good alternative for OPC and natural aggregate to reduce pollution and leads sustainability in the construction.