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The purpose of the study was to develop a powder shampoo with antioxidant attributes.

Dry shampoo compositions were formulated containing alpha olefin sulfonate (AOS), sodium cocoyl isethionate (SCI), microcrystalline cellulose, mannitol, carboxymethyl cellulose, maltodextrin and sodium benzoate with or without extract of Cinnamomum zeylanicum bark. Cinnamon extract was chosen for this study owing to its ubiquitously known antioxidant attributes. The formulations were tested for detergency action and antioxidant potential in vitro.

Cinnamomum zeylanicum extract exhibited noticeable antioxidant activity in vitro. The authors observed that addition of the bark extract to the shampoo formulation was associated with remarkable increase in total phenolic content, total antioxidant activity and radical scavenging activity without any effect on detergency action.

This preliminary study provides a powder shampoo formulation which exhibits antioxidant attributes as a result of incorporation of cinnamon bark extract. Clinical efficacy of the formulation remains to be tested.

Owing to the powder format of the shampoo, the formulation can be manufactured with ease and economically. Functionalizing the formulation with enhancement of antioxidant activity by incorporation of cinnamon bark extract may be associated with beneficial clinical outcomes, which remains to be tested.

The proposed formulation may be stored and sold in eco-friendly packing material, thus could pave the way for reducing the burden of plastic consumption by the shampoo industry.

The present work demonstrates that incorporation of cinnamon bark extract to a powder shampoo formulation, containing AOS and SCI as principle surfactants, significantly enhances its antioxidant attributes.

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.

The purpose of this paper is to provide an overview of the advancement of neuroscience research works in the domains of marketing management and organizational behavior and its future scope for expansion in the area of organizational behavior.

A total of 77 neuroscience research articles in the area of marketing management and organizational behavior published between 2004 and 2017 were reviewed, and a possible future direction for neuroscience research in the area of organizational behavior was identified in this article.

Findings from neuroscience research works suggest that tools and techniques that are useful in the neuroscience domain are also quite powerful and reliable in the context of organizational behavior research. Here, it should be noted that not all of these are independently powerful. Therefore, in certain cases, it is desirable to use neuroscience techniques in association with existing methods.

Neuroscientific research works in the context of the marketing domain were started with the motivation to identify the neural signaling in association with different marketing initiatives. However, the research works have proceeded much deeper and entered into the field of consumer psychology. Further research shows that neuroscience techniques are quite useful in the understanding of consumer behavior and can be extended in the field of organizational behavior. In this study, the authors have provided the future direction of neuroscience research works in the area of organizational behavior.

The primary objective of this study is to understand the motivational process of the nurses who were engaged in COVID care and performed organizational citizenship behavior (OCB) without caring about their own lives. This study also aims to investigate the consequences of such OCB on life satisfaction when the situation continues for a longer period.

For the study’s first objective, an online cross-sectional survey was conducted on 236 critical care nurses from 18 states of India extending over the period from March 2021 to November 2021, when the country passed through the second wave of COVID-19 infection. For the second objective, a longitudinal study compared the life satisfaction level during and post-COVID by giving a one-year gap (November 2022).

The findings of this study reveal that during this COVID period, nurses were strongly performing OCB through their organizational and professional commitment, but one year later, they were identified with a low level of life satisfaction.

Research on nurses has already categorized the profession under high emotional labor. Research also reveals that an individual’s emotional labor strategy (deep acting or surface acting) determines job satisfaction. However, under the COVID situation, nurses have displayed an extraordinary level of OCB by placing their own life at risk. Analysis of this study indicates that the OCB within the nurses during the COVID period originated from their commitment, not from the emotional labor strategy, which they used to select as a coping mechanism. However, one year later, it has affected their mental health and lowered their life satisfaction.

Researches have already pointed out the linkage between pro-male bias and performance evaluation system. The main aim of this study is to understand how far different dimensions of performance measures are susceptible to gender stereotype.

Two separate experimental researches were designed to understand whether the performance assessment is purely based on objective criteria or it is governed by the gender stereotype. Two different performance dimensions of assessment were considered in this study as follows: interactional (behavioural) and procedural. 129 customer care managers from four metro cities of India voluntarily participated in this experimental research and played the role of performance evaluator. These managers were placed in different experimental conditions related to different combinations of gender and justice variations (interactional or procedural).

This study reveals that in violation of behaviour-based performance norm (interactional justice norm), female employees were rated less favourably than male employee both in terms of performance rating and reward recommendation by the managers, but it is not in case of procedural justice violation.

This article has experimentally proved how gender stereotype can distort the performance evaluation of behavioural dimension.

Amidst the turbulent tides of geopolitical uncertainty and pandemic-induced economic disruptions, the information technology industry grapples with alarming attrition and aggravating talent gaps, spurring a surge in demand for specialized digital proficiencies. Leveraging this imperative, firms seek to attract and retain top-tier talent through generous compensation packages. This study introduces a holistic, integrated theoretical framework integrating machine learning models to develop a compensation model, interrogating the multifaceted factors that shape pay determination.

Drawing upon a stratified sample of 2488 observations, this study determines whether compensation can be accurately predicted via constructs derived from the integrated theoretical framework, employing various cutting-edge machine learning models. This study culminates in discovering a random forest model, exhibiting 99.6% accuracy and 0.08° mean absolute error, following a series of comprehensive robustness checks.

The empirical findings of this study have revealed critical determinants of compensation, including but not limited to experience level, educational background, and specialized skill-set. The research also elucidates that gender does not play a role in pay disparity, while company size and type hold no consequential sway over individual compensation determination.

The research underscores the importance of equitable compensation to foster technological innovation and encourage the retention of top talent, emphasizing the significance of human capital. Furthermore, the model presented in this study empowers individuals to negotiate their compensation more effectively and supports enterprises in crafting targeted compensation strategies, thereby facilitating sustainable economic growth and helping to attain various Sustainable Development Goals.

The cardinal contribution of this research lies in the inception of an inclusive theoretical framework that persuasively explicates the intricacies of a machine learning-driven remuneration model, ennobled by the synthesis of diverse management theories to capture the complexity of compensation determination. However, the generalizability of the findings to other sectors is constrained as this study is exclusively limited to the IT sector.

Recent studies document that approximately two-thirds of sample firms have at least one audit committee member serving on their compensation committee (Liao and Hsu, 2013). Prior studies on overlap membership document that presence of audit committee members on compensation committee affects the reporting quality. Since auditors’ audit risk is affected by reporting quality. The purpose of this paper is to examine how the auditors perceive the overlap of audit and compensation committee members when pricing audit fees.

The author use a sample from 2007 to 2012 and run an OLS regression.

The author find a negative association between overlap membership and audit fees. The results are robust after controlling for selection bias, alternate measurement of overlap membership, and an alternate pre- and post-overlap membership test. Additional tests show that the negative relationship between overlap membership and audit fees is explained by lower audit risk and not by lower brand premium of non-Big4 auditors and that the benefit of overlapping membership increases when the audit committee size is large.

The findings suggest that firms with large audit committee can improve their reporting and lower their audit fees by having audit committee members on compensation committee.

The findings contribute to the literature on the consequences of overlap membership and on the ongoing debate about the extent that common membership enhances audit committee monitoring. It also adds to the limited literature on audit committee and audit pricing.

The use of information and communication technology (ICT) has been improving in education and constantly evolving; however, the recent pandemic has catapulted it. Digital transformation of academia through online teaching demands new pedagogies to be adopted by faculty members. Academia embraces technological advancements in teaching-learning to ensure growth, development and sustainability. This paper aims to gain insights regarding the current status of literature, critical contributing authors, countries, areas, overall trends and future direction for research.

The bibliometric data was collected from two of the most widely referred databases: Scopus and Web of Science(WoS); tools like vosViewer and map builder were used for analysis. Short empirical evidence is added to the study to understand faculty members' current adoption of new pedagogical approaches in some prominent higher educational institutions.

Because of the corona pandemic, there is substantial digital transformation in the teaching-learning process. Therefore, it is essential to comprehend what faculty members can adopt critical pedagogies. Understanding the importance of pedagogy in learning outcomes, this study has attempted to synthesize available literature on ICT, pedagogy and higher education in the 21st century.

The study outlined flipped and blended learning as two teaching methods developed due to ICT integration in the classroom. Bibliometric insights from the study build the groundwork for academic advancement to remote online education. This is an attempt to corroborate such insights.

Wireless Multimedia Sensor Network (WMSN) is expected to be a key technology for future network. The multimodal information along with very low-cost availability of the camera sensor nodes is promoting the extensive use of audio, image and video in various real-time implementations. The purpose of this paper is to study various routing issues and the effect of mobility on existing solutions for the applications in future internet.

This paper conducts a survey of the various methodologies for routing and the vital issues in the design of routing protocols for WMSN, and it also discusses about the effect of mobility on various routing methodologies of WMSN. WMSN ubiquitously performs data acquisition, processing and routing for scalar and multimedia data in a mobile environment. The routing protocols should be adaptive in nature and should have a dynamic approach to service effectively for future network. Many authors proposed the mobility of sink to improve lifetime of the network. This paper discusses some effective approaches for the network where not only the sink node but also some of the sensor nodes are mobile.

During the survey, the performance and lifetime of the network are discussed, other parameters like delay, packet loss, energy consumption and simulators used for implementation are also discussed.

The techniques in this paper represent a considerable solution for mobility issues in future internet applications.

This research aims to study the students' perspectives on synchronous and asynchronous learning during the COVID-19 Pandemic. Both synchronous and asynchronous learning approaches used in online education have positive and negative outcomes. Hence, the aim is to study online education's positive and negative consequences, reflecting sync and async approaches. This research followed a mixed research approach. The key stakeholders of this research are the Indian educational institutions and students.

This research collected data from the students undergoing synchronous and asynchronous learning amidst the COVID-19 Pandemic. The data were collected (N = 655) from various students taking online classes during the pandemic. A questionnaire survey was distributed to the students through online platforms to collect the data. In this research, the authors have collected data using simple random sampling, and the same has been used for data analysis using SPSS version 26. The collected data were exposed to a factor analysis using a principal component analysis technique to reduce the vast dimensions.

The study findings show that synchronous learning is sometimes stressful, placing more responsibility on students mainly because of the increased screen time. At the same time, asynchronous learning allows the students to self-explore and research the topics assigned to them. Students also felt that asynchronous activities create a burden because of many written assignments to be submitted within a short period. Overall, the COVID-19 pandemic has been challenging for the students and the teachers. However, teachers have helped students to learn through digital platforms. The majority of the respondents opined that technological disruptions and death in the family circle had been significant reasons for not concentrating during online classes. However, the combination of synchronous and asynchronous learning has led to a balanced education.

Higher education has undergone multiple transformations in a short period (from March 2020, 2021 and beyond). Educational institutions underwent a rapid transition in remote teaching and learning in the initial stages. As time progressed, educational institutions did course navigation where they relooked into their course plans, syllabus and brought a structural change to match the pandemic requirements. Meanwhile, educational institutions slowly equipped themselves with infrastructure facilities to bring academic integrity. At present, educational institutions are ready to face the new normality without disrupting services to society.

Educational institutions create intellectual capital, which is important for the development of the economy. In the light of COVID-19, there are new methods and approaches newly introduced or old methods and approaches, which are reimplemented, and these approaches always work for the benefit of the student community.

The authors collected data during the COVID-19 pandemic; it helped capture the students' experience about synchronous and asynchronous learning. Students and faculty members are newly exposed to synchronous and asynchronous learning, and hence, it is essential to determine the outcome that will help many stakeholders.