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This paper aims to explore the impact of the data observation period on the computation of altmetric measures like velocity index (VI) and half-life. Furthermore, it also attempts to determine whether article-level computations are better than computations on the whole of the data for computing such measures.

The complete publication records for the year 2016 indexed in Web of Science and their altmetric data (original tweets) obtained from PlumX are obtained and analysed. The creation date of articles is taken from Crossref. Two time-dependent variables, namely, half-life and VI are computed. The altmetric measures are computed for all articles at different observation points, and by using whole group as well as article-level averaging.

The results show that use of longer observation period significantly changes the values of different altmetric measures computed. Furthermore, use of article-level delineation is advocated for computing different measures for a more accurate representation of the true values for the article distribution.

The analytical results show that using different observation periods change the measured values of the time-related altmetric measures. It is suggested that longer observation period should be used for appropriate measurement of altmetric measures. Furthermore, the use of article-level delineation for computing the measures is advocated as a more accurate method to capture the true values of such measures.

The research work suggests that altmetric mentions accrue for a longer period than the commonly believed short life span and therefore the altmetric measurements should not be limited to observation of early accrued data only.

The present study indicates that use of altmetric measures for research evaluation or other purposes should be based on data for a longer observation period and article-level delineation may be preferred. It contradicts the common belief that tweet accumulation about scholarly articles decay quickly.

Several studies have shown that altmetric data correlate well with citations and hence early altmetric counts can be used to predict future citations. Inspired by these findings, majority of such monitoring and measuring exercises have focused mainly on capturing immediate altmetric event data for articles just after the publication of the paper. This paper demonstrates the impact of the observation period and article-level aggregation on such computations and suggests to use a longer observation period and article-level delineation. To the best of the authors’ knowledge, this is the first such study of its kind and presents novel findings.

The COVID-19 pandemic has had far-reaching effects on society and will continue to be a subject of study for researchers in the years to come. Businesses have implemented technologies that reduce reliance on physical currencies, such as e-commerce sites and contactless payments. This study aims to examine the users’ attitudes and behaviors toward mobile payments. The focus is on identifying the most effective techniques and approaches that businesses can use to encourage user adoption of mobile payments.

This study uses survey data from 396 active mobile payment users across the mid-west region of the USA to test the proposed hypothesis. The snowball sampling approach is used to sample the participants for the data collection. This study uses partial least squares structural equation modeling to test the ten hypotheses proposed in this study.

This study finds that organizational commitment and privacy customization can significantly overcome users’ protective attitudes toward mobile payments during the pandemic. In addition, providing users with privacy customization options can significantly encourage self-disclosure, which is crucial for transaction authentication and fraud detection.

Envisioned in the backdrop of the COVID pandemic, this is one of the earliest studies investigating the role of privacy customization, self-disclosure and organizational commitment on mobile payment adoption.

This study aims to analyze the critical factors affecting workplace well-being at construction sites across countries with different income levels. Accordingly, this study’s objectives are to identify: critical factors affecting workplace well-being at construction sites in low-, lower-middle-, upper-middle- and high-income countries, overlapping critical factors across countries with different income levels and agreements on the critical factors across countries with different income levels.

This study identified 19 factors affecting workplace well-being using a systematic literature review and interviews with construction industry professionals. Subsequently, the factors were inserted into a questionnaire survey and distributed among construction industry professionals across Yemen, Zimbabwe, Malaysia and Saudi Arabia, receiving 110, 169, 335 and 193 responses. The collected data were analyzed using descriptive and inferential statistics, including mean, normalized value, overlap analysis and agreement analysis.

This study identified 16 critical factors across all income levels. From those, 3 critical factors overlap across all countries (communication between workers, general safety and health monitoring and timeline of salary payment). Also, 3 critical factors (salary package, working environment and working hours) overlap across low-, low-middle and upper-middle-income countries, and 1 critical factor (project leadership) overlaps across low-middle, upper-middle and high-income countries. The agreements are inclined to be compatible between low- and low-middle-income, and between low- and high-income countries. However, agreements are incompatible across the remaining countries.

This study can serve as a standard for maintaining satisfactory workplace well-being at construction sites.

To the best of the authors’ knowledge, this study is the first attempt to analyze factors affecting workplace well-being at construction sites across countries with different income levels.

Construction activities generate overwhelming waste that is typically disposed of in landfills, which has significant environmental consequences and hinders national progress. However, with the appropriate competencies, there is an opportunity to identify construction activities that produce recyclable materials, offering a path to a sustainable future. This study aims to assess the competencies for identifying construction activities that produce recyclable materials. To attain that aim, the study seeks to identify the key competencies and assess the index level of the competencies.

A systematic literature review was conducted, and 20 competencies were identified and categorized into knowledge, skills, and abilities. A questionnaire survey was developed based on the competencies and completed by 101 individuals. The collected data were analyzed using normalized mean analysis, confirmatory factor analysis, and fuzzy synthetic evaluation (FSE).

The results revealed that the key competencies are problem-solving skills, communication skills, skills in providing vocational training, and knowledge of the environmental impacts of construction activities. The FSE ranks the constructs in order of skills, knowledge, and abilities. Also, the FSE illustrated that the overall index level is inclined to be important.

This study leads to saving natural resources, using raw materials efficiently, protecting from environmental pollution, and mitigating resource depletion by providing the index level of the competencies.

The findings can guide professionals in effective waste management, policymakers in creating new policies and regulations, and researchers in compiling a list of competencies for identifying construction activities that produce recyclable materials.

This study aims to perform the bibliometric analysis of the customer engagement (CE) literature, highlights the major research themes and classifies the subdomains. The study also identifies antecedents and consequences, as well as dimension evolution, and suggests future research directions.

This study used a comprehensive bibliometric approach using Scopus data from 2002 to January 2024. Advanced analytical techniques, including bibliometric and cocitation analysis using R and bibexcel, were used. In addition, machine learning (ML)-based Latent Dirichlet Allocation (LDA) was used to extract latent themes.

This study reveals the domain’s past trend and present research scenario. The thematic analysis of CE is classified into three phases. Document cocitation analysis provided four broad clusters: conceptualization and operationalization, value creation through engagement, building relationships with brands and engagement-social media interface. The antecedents and consequences are categorized and presented along with the evolution of the multidimensional nature of CE.

This study adds to the literature in two key ways. First, the entire scholarly production has been compiled into one frame. Second, multiple methods were used to unravel citation, cocitation and textual data. Furthermore, ML-based LDA was used to extract latent themes from clusters and future research directions were proposed.

This study aims to identify and analyse critical barriers to cloud manufacturing (CM) adoption for achieving sustainability amongst manufacturing micro, small and medium-sized enterprises (MSMEs) in an emerging economy.

Initially, through a literature survey and expert inputs, this study identified and finalized 21 critical barriers to CM adoption, which were further analysed by employing a hybrid multiple criteria decision-making (MCDM) approach. In this approach, the best–worst method (BWM) was used to rank the identified barriers. However, to analyse the interrelation amongst these barriers and classify them into the cause-effect group, the decision-making trial and evaluation laboratory (DEMATEL) method was employed. Furthermore, the study recommended various strategies that can help overcome high-priority barriers and enhance CM adoption within firms.

The results of the study show that organizational, legal and economic barriers are the high-priority barriers that need to be addressed to enhance CM adoption.

The findings of the study will help managers and decision-makers in manufacturing MSMEs develop effective strategies and policies to enhance CM adoption.

Notably, this investigation is one of the preliminary research activities to explore the sustainability aspect of CM adoption amongst MSMEs in an emerging economy.

Autonomous floor-cleaning robots (AFCRs) have become increasingly popular due to their ability to provide efficient and effective cleaning without the need for human intervention. These robots can perform various cleaning tasks, such as vacuum cleaning, mopping, scrubbing or sweeping, in domestic or industrial setups. As the use of floor-cleaning robots continues to grow, this paper aims to document key technological advancements.

The structure of the present work relies on published research articles excavated from general online research databases such as Google Scholar, Web of Science and Scopus. The authors use a variety of keywords and titles to search for research papers. Finally, 93 research articles are selected for review based on abstracts and key results that match AFCRs.

According to market trends, floor-cleaning robots dominate other cleaning areas. This review mainly focuses on five attributes of floor-cleaning robots: design and development of AFCR, complete coverage path planning, the application of machine learning (ML)/deep learning (DL), optimisation strategies for qualitative output and ethnographic studies. It also consists of discussions based on the results of reported technical works. Hence, AFCRs have dominated the market in the past decade and are likely to be more aggressive in the coming years.

To the best of the authors’ knowledge, only a survey article based on US-granted patents published in 2013 constitutes a review work in the research domain on AFCRs. In 2021, another review conducted a survey on the latest technological advancements in window-cleaning robots. It reviewed in detail the locomotion aspects, control mechanisms, adhesion mechanisms, sensors and actuators required for window-cleaning robots. In 2019, a comprehensive review was published on cleaning robots from a control strategy perspective for domestic applications. Therefore, the authors have crafted this review to understand the evolution of floor-cleaning robots in the past decade.

This study aims to analyze the mediating role of attitude in understanding the impact of online service convenience on user engagement and intention to continuously use e-resources. Five components of online service convenience have been adopted for the present study: These are access convenience, search convenience, evaluation convenience, transaction convenience and possession/ post-possession convenience.

A total of 500 PhD scholars and faculty members from two different states of India were approached to provide their responses through a structured questionnaire, which resulted in 224 complete responses. These responses were analyzed using structural equation modeling. The statistical analysis has been performed with the help of Smart-PLS 3.

The study findings have proven the proposed conceptual model by showing a significant relationship between all the variables. Furthermore, it has been identified that the attitude of the users also positively impacts intention to continuously use e-resources.

This study contributes to the literature on e-resources by providing implications for students, faculties, managers and society.

This paper aims to delineate the nature of the costs associated with the diffusion of brand posts. Since cost is an essential component of customer lifetime value, this research also aims to identify factors that impact consumer engagement (CE) with brand posts.

This study conceptualize marginal cost of CE as the ratio of a unit change in cost for a unit change in CE – this ratio is conceptualized for a paid brand post compared to an organic brand post. The authors present a theoretically grounded simulation method that analyzes the relative impact of several factors that influence CE with brand posts. By using an agent-based simulation model, the method presented in this paper helps explain the relative impact of four factors on CE with brand posts on social media.

The authors explain four factors that influence the diffusion of CE with a brand post – promotion-related (i.e. whether it is paid vs organic), network-related, user-related and active periods. The authors also show that the effectiveness of paid posts vs organic posts attributed to a better audience assembled by the seeding algorithms dissipates after the initial stages of diffusion. These findings indicate that paid posts are effective vs organic posts in large part due to higher exposure than due to the efficiency of the algorithms to assemble nodes that are likely to engage with the post.

An agent-based model details the impact of several factors that influence the effectiveness of paid and organic posts and presents methods to analyze the impact of these factors that have implications for theory.

The authors address the difficulty in ascertaining the effectiveness of paid posts by proposing a metric – marginal cost of engagement, defined as the incremental cost incurred by the marketer in earning one additional unit of CE. Since the costs incurred on paid and organic posts differ only on variable components, the marginal cost of engagement presents a way to benchmark paid posts against organic posts, which is very useful for managers in ascertaining the amount to spend on paid posts on social media.

There is little prior research on the costs involved in the diffusion of brand posts on social media. Identifying specific factors that impact costs is valuable for theory and practice.

This study aims to explore the extent to which customer orientation and creative benefits offered by a firm may weaken rather than strengthen customer engagement. In doing so, it sheds new light on how customer orientation and creative benefits may facilitate rather than hinder engagement by customers.

A field study provides a test of the proposed effects in a hedonic consumption setting with 1,703 customers of an online dating service. Furthermore, an experimental study with 277 executives in a functional consumption setting (new mobile app) helps affirm the robustness of the field study findings.

This research theorizes and examines how communal relationship norms between customers and a firm, along with customers’ psychological empowerment, mediate the effect of customer orientation and creative benefits on customer engagement. A provocative finding of the study is that communal relationship norms help boost, whereas psychological empowerment reduces, the effects of both customer orientation and creative benefits on customer engagement.

The research examines different relationship norms and how they can become integral to customer–company relationships; this perspective helps reveal the underlying dynamics. It contributes to the literature on customer engagement by theorizing and demonstrating the link between customer orientation and customer engagement, two central constructs in the marketing literature. It theorizes and demonstrates that providing creative benefits brings about a direct competitive advantage for the product itself, and acts as a significant variable that explains the company−customer relationship.

The findings highlight the advantages and challenges associated with encouraging customer engagement. First, they suggest that companies emphasize their customer orientation and creative benefits. Second, managers should try to minimize the possible process of raising customers’ psychological empowerment while maximizing the impact of communal relationship norms.

This study identifies psychological empowerment as a key reason customer-oriented companies that provide creative benefits still struggle to engage their customers. It also suggests viable tactics to overcome barriers to enhanced customer engagement, such as by minimizing the effects of customers’ psychological empowerment while maximizing the impact of their perceived communal relationship norms.