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This study aims to explore the role of the linguistic style used in the brand-posted social media content on consumer engagement in the Fintech domain.

A total of 3,286 tweets (registering nearly 1.35 million impressions) published by 10 leading Fintech unicorns in India were extracted using the Twitter API. The Linguistic Inquiry and Word Count (LIWC) dictionary was used to analyse the linguistic characteristics of the shared tweets. Negative Binomial Regression (NBR) was used for testing the hypotheses.

This study finds that using drive words and cognitive language increases consumer engagement with Fintech messages via the central route of information processing. Further, affective words and conversational language drive consumer engagement through the peripheral route of information processing.

The study extends the literature on brand engagement by unveiling the effect of linguistic features used to design social media messages.

The study provides guidance to social media marketers of Fintech brands regarding what content strategies best enhance consumer engagement. The linguistic style to improve online consumer engagement (OCE) is detailed.

The study’s findings contribute to the growing stream of Fintech literature by exploring the role of linguistic style on consumer engagement in social media communication. The study’s findings indicate the relevance of the dual processing mechanism of elaboration likelihood model (ELM) as an explanatory theory for evaluating consumer engagement with messages posted by Fintech brands.

This paper aims to investigate the current state of biocomposites used in fused deposition modelling (FDM) with a focus on their mechanical characteristics.

The study presents a variety of biocomposite materials that have been used in filaments for 3D printing by different researchers. The process of making filaments is then described, followed by a discussion of the process parameters associated with the FDM.

To achieve better mechanical properties of 3D-printed parts, it is essential to optimize the process parameters of FDM while considering the characteristics of the biocomposite material. Polylactic acid is considered the most promising matrix material due to its biodegradability and lower cost. Moreover, the use of natural fibres like hemp, flax and sugarcane bagasse as reinforcement to the polymer in FDM filaments improves the mechanical performance of printed parts.

The paper discusses the influence of critical process parameters of FDM like raster angle, layer thickness, infill density, infill pattern and extruder temperature on the mechanical properties of 3D-printed biocomposite.

Implementing blockchain in sustainable development goals (SDGs) and environmental, social and governance (ESG)-aligned infrastructure development involves intricate strategic factors. Despite technological advancements, a significant research gap persists, particularly in emerging economies. This study aims to address the challenges related to SDGs and ESG objectives during infrastructure delivery remain problematic, identifying and evaluating critical strategic factors for successful blockchain implementation.

This study employs a three-stage methodology. Initially, 13 strategic factors are identified through a literature review and validated by conducting semi-structured interviews with six experts. In the second stage, the data were collected from nine additional experts. In the final stage, the collected data undergoes analysis using interpretive structural modeling (ISM)–cross-impact matrix multiplication applied to classification (MICMAC), aiming to identify and evaluate the independent and dependent powers of strategic factors driving blockchain implementation in infrastructure development for SDGs and ESG objectives.

The study’s findings highlight three significant independent factors crucial for successfully integrating blockchain technology (BT) into infrastructure development for SDGs and ESG goals: data security (F4), identity management (F8) and supply chain management (F7). The study unravels these factors, hierarchical relationships and dependencies by applying the MICMAC and ISM techniques, emphasizing their interconnectedness.

This study highlights critical strategic factors for successful blockchain integration in SDG and ESG-aligned infrastructure development, offering insights for policymakers and practitioners while emphasizing the importance of training and infrastructure support in advancing sustainable practices.

This study concentrates on assessing the research productivity in the domain of social media security in the past decades. The purpose of this study is to conduct a comprehensive bibliometric review on social media using various bibliometric indicators.

A total of 8,121 scientific publications were retrieved from Scopus database from period 1998 to 2021 using associated keyword search. This study also used VOSviewer^© tool to evaluate the network visualisation.

The result of this study revealed that there is a steady growth of annual publications except for the years 2015 and 2016. A total of 8,121 scientific publications and 80,454 total citations were found with 11.2 average citations per publication. The USA, China and India were top productive countries in terms of publishing research in the field; Chinese Academy of Sciences secured top position with 126 publications in highly productive organisation in the domain. The lecture notes in computer science from Springer Nature received a highly produced title with 553 publications and 4,453 total citations. For co-occurrence of author’s keywords, network visualisation analysis revealed that “Social Media”, “Social Network”, “Security”, “Privacy” and “Trust” found maximum occurrence in the domain of social media security.

This study provides comprehensive research status of social media security by performing a bibliometric analysis. The findings of this study will help relevant researchers to understand the research trend, pursue scientific collaborators and enhance research topic preferences.

The rareness of this study, detailed bibliometric analysis on the domain of social media security, is proven using numerous bibliometric indicators and application of VOSviewer in the domain.

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.