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This paper aims to study the combination of photochromic microcapsules, which use the ultraviolet (UV) rays for colour changing phenomena, and titanium oxide (TiO₂) nanoparticles (NPs), which block the UV rays by their photocatalytic activity in the sunlight on the cotton fabric.

The TiO₂ NPs mixed with photochromic printing paste are used for coating on cotton fabric and further curing is performed in a one-step process. The photochromic pigment printed fabric impregnated in a liquid solution is processed in a two-step process with two variables such as 1% TiO₂ and 2% TiO₂. The characterization of samples was done with a UV transmittance analyser, surface contact angle, antimicrobial test and fabric physical properties.

The UV protection of TiO₂-treated photochromic printed fabric was high and gives the ultraviolet protection factor rating of 2,000 which denotes almost maximum blocking of UV rays. The antibacterial activity of the one-step samples shows the highest 36 mm zone of inhibition (ZOI) against S. aureus (gram-positive) and 32 mm ZOI against E. coli (gram-negative) bacteria. The one-step sample shows the highest static water contact angle of 118.6° representing more hydrophobicity, whereas the untreated fabric is fully wetted (0.4°). In two-step processes, as the concentration of TiO₂ increased, the antibacterial activity, UV blocking and hydrophobicity became better.

This work achieves the multifunctional finishes by using photochromic microcapsules and NPs in a single process as a first attempt. The results inferred that one-step sample has achieved higher values in most of the tests conducted when compared to all other sample.

To sustain competitive advantage, it is necessary to understand consumers and their psychological fears and deliver them a service solution which is best under existing conditions so as to ensure consumer loyalty and retention. This paper seeks to conceptualise and operationalise customer relationship management (CRM) through two component model (operational CRM (OCRM) and analytical CRM (ACRM)), particularly in the healthcare sector.

The relationship between OCRM, based on three patient‐staff constructs (physicians, nurses and support staff) and ACRM based on four constructs (satisfaction, repatronization, recommendation and organizational performance) was analysed using confirmatory factor analysis (AMOS). The data for the model were collected from 306 indoor patients of three large public hospitals who have been associated with the hospital for at least five years.

The model portraying service quality as an antecedent to OCRM is found to be acceptable whereas the other two models, namely, service quality as the moderating variable in explaining OCRM and ACRM relationship effectively and direct relationship between OCRM (service quality implicit) and OCRM) were rejected. Characteristics, primarily caring attitude, friendliness, helpfulness, response to queries, expertise and effective treatment are found to be significant for OCRM from physicians, nurses and support staff perspectives that can impact the four ACRM dimensions – satisfaction, repatronization, recommendation and organizational performance.

The study contributes to the current understanding of CRM in particular and consumer behaviour in general, in the context of the healthcare sector. The role of service quality in influencing patient‐staff interaction and CRM linkage with the service dominant concept has added more strength to the conceptual development of TCRM.

This paper aims to examine the three dynamics of customer relationship management (CRM), namely, service quality (SQ), customer satisfaction (CS) and customer loyalty (CL) (long‐term relationship) in the healthcare sector. It specifically investigates the effects of physical environment quality (PEQ) and interaction quality (IQ) and significant components of SQ on outcome SQ dimensions, namely, CS and CL.

A total of 400 indoor patients from departments such as, general medicine, pediatrics, general surgery, gynecology, ENT and orthopedics were selected using proportionate stratified random sampling from May‐August 2007. Personal contact approach was used for contacting the respondents. Data validity and reliability were duly assessed using exploratory factor analysis. The data were then analyzed using structural equation modeling through AMOS.

Based on data analysis, the direct effect of CRM dynamics, i.e. PEQ and IQ on SQ and their ultimate effect on CS and CL is found to be significant. However, the model fit values came out poor as p (CMIN) (0.000), CMIN/DF (2,605.41), RMSEA (0.263), NFI (0.076), RFI (−0.066), IFI (0.078), TLI (−0.069) and CFI (0.074).

The cross‐sectional research design of the study does not offer nearly the same insight into the dynamics of CR as a longitudinal design study. The study analysed overall CS and CL as the major focus of the study was on the PEQ and IQ to understand impact of SQ on CRM outcomes and has ignored some antecedents that could help and explain customer perception more concretely. Further future studies could consider broader organization image typologies and measures in understanding CRM dynamics such as organizational excellence and customer value. This could become the future agenda for the upcoming studies.

PEQ needs to be improved by focusing on cleanliness of wards and toilets, peaceful atmosphere, supportive and additional facilities, clean drinking water, clean beddings, special services to the needy. IQ hospitals should organize training programmes to inculcate better attitudinal and behavioural skills to understand patients, giving them proper care, listening to and answering their queries. For better process quality, hospitals need to focus on effective administration functioning. The study concludes that there is need to improve CRM dynamics (PEQ and IQ) in the public healthcare to accomplish CRM objectives (CS and CL).

This study provides some important insights for CRM theory and practice. An understanding of SQ, CS and loyalty dynamics is a first step toward effective service management and the retention of customers in the long term. Three‐way interactions between the main effects of SQ, CS and loyalty yield additional insight into the relative importance of physical environment and IQ in customers' decision to be loyal, and that can provide a pave way for accomplishing CRM objectives.

This paper aims to analyze and give directions for advancing research in stock market volatility highlighting its features, structural breaks and emerging developments. This study offers a platform to research the benchmark studies to know the research gap and give directions for extending future research.

The author has performed the literature review, and, reference checking as per the snowballing approach. Firstly, the author has started with outlining and simplifying the significance of the subject area, the review illustrating the various elements along with the research gaps and emphasizing the finding.

This work summarizes the studies covering the volatility, its properties and structural breaks on various aspects such as techniques applied, subareas and the markets. From the review’s analysis, no study has clarified the supremacy of any model because of the different market conditions, nature of data and methodological aspects. The outcome of this research work has delivered further magnitude to research the benchmark studies for the upcoming work on stock market volatility. This paper has also proposed the hybrid volatility models combining artificial intelligence with econometric techniques to detect noise, sudden changes and chaotic information easily.

The author has taken the research papers from the scholarly journal published in the English language only and the author may also consider other nonscholarly or other language journals.

To the best of the author’s knowledge, this research work highlights an updated and more comprehensive framework examining the properties and demonstrating the contemporary developments in the field of stock market volatility.

This paper aims to identify the role of internet of things (IoT) in water supply chain management and helps to understand its future path from the junction of computer science and resource management.

The current research was studied through bibliometric review and content analysis, and various contributors and linkages were found. Also, the possible directions and implications of the field were analyzed.

The paper’s key findings include the role of modern computer science in water resource management through sensor technology, big data analytics, IoT, machine learning and cloud computing. This, in turn, helps in understanding future implications of IoT resource management.

A more extensive database can add up to more combinations of linkages and ideas about the future direction. The implications and understanding gained by the research can be used by governments and firms dealing with water management of smart cities. It can also help find ways for optimizing water resources using IoT and modern-day computer science.

This study is one of the very few investigations that highlighted IoT’s role in water supply management. Thus, this study helps to assess the scope and the trend of the case area.

The purpose of this paper is to propose a fourfold semantic similarity that results in more accuracy compared to the existing literature. The change detection in the URL and the recommendation of the source documents is facilitated by means of a framework in which the fourfold semantic similarity is implied. The latest trends in technology emerge with the continuous growth of resources on the collaborative web. This interactive and collaborative web pretense big challenges in recent technologies like cloud and big data.

The enormous growth of resources should be accessed in a more efficient manner, and this requires clustering and classification techniques. The resources on the web are described in a more meaningful manner.

It can be descripted in the form of metadata that is constituted by resource description framework (RDF). Fourfold similarity is proposed compared to three-fold similarity proposed in the existing literature. The fourfold similarity includes the semantic annotation based on the named entity recognition in the user interface, domain-based concept matching and improvised score-based classification of domain-based concept matching based on ontology, sequence-based word sensing algorithm and RDF-based updating of triples. The aggregation of all these similarity measures including the components such as semantic user interface, semantic clustering, and sequence-based classification and semantic recommendation system with RDF updating in change detection.

The existing work suggests that linking resources semantically increases the retrieving and searching ability. Previous literature shows that keywords can be used to retrieve linked information from the article to determine the similarity between the documents using semantic analysis.

These traditional systems also lack in scalability and efficiency issues. The proposed study is to design a model that pulls and prioritizes knowledge-based content from the Hadoop distributed framework. This study also proposes the Hadoop-based pruning system and recommendation system.

The pruning system gives an alert about the dynamic changes in the article (virtual document). The changes in the document are automatically updated in the RDF document. This helps in semantic matching and retrieval of the most relevant source with the virtual document.

The recommendation and detection of changes in the blogs are performed semantically using n-triples and automated data structures. User-focussed and choice-based crawling that is proposed in this system also assists the collaborative filtering. Consecutively collaborative filtering recommends the user focussed source documents. The entire clustering and retrieval system is deployed in multi-node Hadoop in the Amazon AWS environment and graphs are plotted and analyzed.

This study examines how perceptions of injustice, anger, and group identification motivate follower intentions to engage in collective action against leaders. The study revolved around the Malaysian prime minister’s actions and responses toward allegations of misuse of public funds. Responses from 112 Malaysians via a cross-sectional survey revealed that follower perceptions of leader injustice are significantly related to anger toward the leader, which in turn is related to intentions to engage in collective action. The relationship between perceptions of distributive injustice and anger is moderated by group identification, while group efficacy moderates the relationship between anger and collective action intentions.

Human health is strongly affected by diet. By the increased use of food industries products, public knowledge about health factors and side effects of chemical additives, the concepts of human health founded an important aspect during past years, and application of natural-based ingredients such as coloring, flavoring, texturizing and anti-oxidative agents was increased.

The aim of the present paper is to review the published scientific research studies about lycopene health benefits in different human disease or disorders and bold the necessity of study the health effects of lycopene after its formulation in food industrial products. About 190 papers were searched in Google Scholar, PubMed, Web of Science databases and 72 relevant papers were used. It was found that in medical studies, the lycopene oleoresin or powder is used directly to the subjects. However, it is necessary to study the effectiveness of lycopene in diet food products.

According to the literature, it has beneficial effects on cancers, glands, reproductive system, bone, gastric system, liver and fat reduction in the body. Also, it was concluded from the literature that lycopene oxidative cleavages make also its chemo protective effects which is a lost key element to study different food processing on lycopene products or its isomers in final food products and on human health.

Many ingredients in food formulations are substituted by natural products. Lycopene is a colorant but also, according to the literature, has a strong antioxidative and anti-inflammatory effect to reduce the risk of most important human disease and disorders. Future research in food science can emphasize the effect of different unit operations or formulations on lycopene effects on human health.