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The purpose of this study is to explore the use of smartphone-embedded microelectro-mechanical sensors (MEMS) for accurately estimating rotating machinery speed, crucial for various condition monitoring tasks. Rotating machinery (RM) serves a crucial role in diverse applications, necessitating accurate speed estimation essential for condition monitoring (CM) tasks such as vibration analysis, efficiency evaluation and predictive assessment.

This research explores the utilization of MEMS embedded in smartphones to economically estimate RM speed. A series of experiments were conducted across three test setups, comparing smartphone-based speed estimation to traditional methods. Rigorous testing spanned various dimensions, including scenarios of limited data availability, diverse speed applications and different smartphone placements on RM surfaces.

The methodology demonstrated exceptional performance across low and high-speed contexts. Smartphones-MEMS accurately estimated speed regardless of their placement on surfaces like metal and fiber, presenting promising outcomes with a mere 6 RPM maximum error. Statistical analysis, using a two-sample t-test, compared smartphone-derived speed outcomes with those from a tachometer and high-quality (HQ) data acquisition system.

The research limitations include the need for further investigation into smartphone sensor calibration and accuracy in extremely high-speed scenarios. Future research could focus on refining these aspects.

The societal impact is substantial, offering cost-effective CM across various industries and encouraging further exploration of MEMS-based vibration monitoring.

This research showcases an innovative approach using smartphone-embedded MEMS for RM speed estimation. The study’s multidimensional testing highlights its originality in addressing scenarios with limited data and varied speed applications.

Introduction: Historically, the corporate governance (CG) framework was designed primarily to safeguard the economic interests of shareholders, as a result of political and legal interventions, developing into an effective instrument for stakeholders and society in general.

Purpose: The core objectives of the study include: identifying journals/publications responsible for publishing CG studies in India, key CG issues covered by CG researchers, the amount of high-impact CG literature across different time periods, sectors/industries covered by CG researchers and different research instruments (quantitative or qualitative) used in CG studies in India.

Design/methodology: The chapter used a sample of 130 corporate governance studies that fulfil the selection criteria, drawn from the repository of over 100 reputed journals that are either recognised by the Australian Business Deans Council (ABDC) or indexed by SCOPUS. A systematic literature review has been carried out pertaining to CG issues in India, based on various statistical tools, data, industries, research outlets & citations, etc.

Findings: The results show an overwhelming number of studies have assessed the relationship between CG variables and firm performance, which could be measured through a variety of performance metrics such as ROA and ROI. Apart from empirical analysis, many conceptual studies use repetitive basic statistical tools like descriptive statistics or regression analysis. The chapter offers insights into current achievements and future development.

Originality/value: This bibliometric study is a useful guide for policymakers, corporate leaders, research organisations and management faculty to draw insights from work produced by eminent researchers in GC in India.

The purpose of this paper is to evaluate various reliability measures like availability, reliability, mean time to failure and profit function.

The authors present a novel method for availability analysis of an engineering system incorporating waiting time to repair. The considered system consists of two subsystems, namely, A and B connected in series. The subsystem B has two identical units in standby arrangement. Each unit of the subsystem has two modes, i.e. normal efficiency or failed. The two standby units of the subsystem B are connected by an imperfect switching. The system is analyzed by supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula.

Numerical examples with a way to highlight the important results have been appended at last. Numerical calculation shows that availability and reliability of the system is decreasing with respect to time when failure rates are fixed at different values. Finally, cost analysis of system reveals that the expected profit decreases with increase in service cost.

This paper presents a mathematical model in which an important aspect of switching has been taken into consideration, which is consistent with actual failures of switching by assuming two different types of failure between adjacent transition. It is evaluated with the help of the Gumbel-Hougaard family of copula.

This paper aims to evaluate the construction supply chain (CSC) by examining its relationships with various key areas and its development, identifying gaps and outlining potential future research directions that affect the implementation of CSC standards during the timeframe of the United Nations’ “Decade of Action” plans in the past two decades.

This paper reports on a systematic literature review with bibliometric analysis that investigates publications from around the world on various aspects of CSC. These aspects include research methodology/data collection technique, inquiry mode, country-specific research, focused areas of study, the research aims and publication periods.

The findings of the study reveal that information technology, information sharing, collaboration, performance measurement and CSC configuration have received considerable attention and analysis. However, financial management, supply chain resilience, logistics, vendor managed inventory and rural CSC have been identified as significant areas that require further investigation since limited attention has been given to them in the existing literature.

CSC is a very dominant topic in the current study, but there are some limitations to it. Scopus and Web of Science databases were used to conduct the study. A future study can therefore consider papers related to other databases. As the focus was specifically dedicated to construction material SC only, the papers associated with SCs of labours and equipment have been eradicated.

To the best of the authors’ knowledge, this is the first structured and systematic literature review that identifies the issues related to the CSC during the timeframe of the United Nations’ “Decade of Action” plans and proposes future research directions to enhance the effectiveness and efficiency of CSC.

Several industries including banking are booming because of COVID-19. However, it is still unknown whether this growth is momentary or permanent in nature. Hence, this study aims to identify the role of health-related concerns and trust as stimuli on M-payment loyalty.

Data were collected through Google Forms from 431 participants. Subjects were M-payment users. The hypothesized model was tested using structural equational modeling.

Results of the study indicate that perceived severity and trust act as stimuli for M-payment loyalty. Further, trust not only influences loyalty directly but also through intimacy. Additionally, no linear relationship was found between perceived usefulness and M-payment loyalty.

This work is an early attempt to consider health-related concerns and trust as stimuli to predict M-payment loyalty. Further, this study focused on three new constructs, namely perceived severity, perceived susceptibility and intimacy, that are underexplored in digital banking literature.

To test if the factors “reviewer location” and “time frame” have any impact on the prediction results when predicting online product ratings from user reviews.

Reviews and ratings are scraped for the product “The Secret” book through Web pages of e-commerce websites like Amazon and Flipkart. Such data is used for training the model to predict ratings of similar products based on reviews data in various other social media platforms like Facebook, Quora and YouTube. After data preprocessing, sentiment analysis is used for opinion classification. A multi-class supervised support vector machine is used for feature classification and predictions. The four models produced in the study have a prediction accuracy of 79%. The data collection is done based on a specific geographical location and specific time frame. Post evaluating the predictions, inferential statistics are used to check for significance.

There will be an impact on the ratings predicted from the reviews that belong to a particular geographic location or time frame. The ratings predicted from such reviews help in taking accurate decisions as they are robust and informative.

This study is confined to a single product and for cross domain social media pages, only Facebook, YouTube and Quora data are considered.

Provides credible ratings of a product/service on all cross domain social media pages making the initial screening process of purchase decisions better.

Many studies explored the usefulness of reviews for rating prediction based on review nature. This study aims to identify the usefulness of reviews based on factors that would reduce uncertainty in the purchase process.

In this paper, the relationship of brand logo and purchase intention is investigated along with the mediating role of customer satisfaction, brand preference and brand attitude. The research is conducted on an online passenger transport company called Tapsi.

In this study, we examine the positive effect of brand logo on brand attitude, consumer satisfaction and strengthening the intention to buy and brand preference by customer satisfaction. The statistical population was randomly selected. We design a conceptual model and then prepare a standard online questionnaire and send it to the target groups. Among this, the participants, 59% are women and 41% are men. After collecting the data through the software Smart-PLS3, we start the analysis. According to Cronbach's alpha and AVE, the validity and reliability of the model are confirmed.

The study shows that the brand logo has a positive and direct influence on customer attitude and satisfaction, and customer satisfaction mediates the purchase intention and brand preference. Given that the brand logo describes the company, managers must be very sensitive to design of a proper logo and spend enough time and money on it.

Few studies have examined the effectiveness of the brand logo the present study and the results show that the brand logo and its structures are directly related to brand attitude as a result of consumer satisfaction in all services even transportation services. The first thing consumers see when they first use a company’s services is the company logo. The brand and its logo can change the attitude and decision of the customer. Past studies have also shown that the brand logo can have a direct impact on customer satisfaction and customer preference for the brand. Therefore a model was prepared and the mentioned variables were selected. Brand preference as a mediating variable has a positive role on buying intention. However all relationships and their predictive power have been confirmed.