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This paper aims to explore the outcomes of an analysis on day by day task – journey planning conduct of senior citizens by using a modern dynamic model and a family unit travel overview, gathered in Bhubaneswar, Odisha, of India in 2018. The task-journey planning display assumes an unique time–space-constrained planning development.

The main commitment of this paper is to reveal day by day task – journey planning conduct through a comprehensive dynamic framework. Numerous behavioural subtleties are revealed by the subsequent empirical model. These incorporate the role that income plays in directing outside time consumption decisions of senior citizens. Senior citizens in the most elevated and least salary classes will in general have minor varieties in time consumption decisions than those in middle pay classifications. Generally speaking, the time consumption decisions become progressively steady with expanding age, demonstrating that more task durations and lower task recurrence become progressively predominant with increasing age.

Day by day task-type and area decisions reveal a reasonable irregular utility-amplifying level headed conduct of senior residents. Unmistakably expanding spatial availability to different task areas is an urgent factor in characterizing every day outside task interest of senior residents. It is likewise evident that the assorted variety of outside task-type decisions decreases with rise in age and senior citizens are major touchy to auto journey hour than to travel or non-mechanized journey hour.

The fundamental constraint to the dynamic structure is that the mode decision model was viewed as exogenic to the demonstrating framework. The essential purpose behind this supposition that was that senior citizens in the Bhubaneswar are overwhelmingly customers of the local car. Coordination of the mode decision display part inside this structure would deliver a full task-based journey request model that could catch trip age, starting times, outing circulation and mode decision using a solitary demonstrating framework.

The purpose of this study is to explore the effect on distress of senior citizen’s anxiety levels in quarantine during the second wave of COVID-19 pandemic. This is a descriptive study, in which data were collected using the online survey method, a sociodemographic form, a semi-structured data form for second wave COVID-19, the anxiety-level scale and the distress scale.

Data were collected during the period when a curfew was imposed for the senior citizen. Data were analyzed using a structural equation model. According to the structural equation model, anxiety was determined as a predictor of distress.

The anxiety levels of the senior citizen who were 60–69 years old, female, single; had inadequate knowledge about the pandemic; and had not encountered a similar pandemic before considered that family bonding was affected negatively, so they became alone and reported that they became bored, exhausted and distressed during the pandemic, which increased their distress levels. Anxiety affects distress in the senior citizens.

One of the policy implications of this study is that governments should provide behavioral support to citizens during a pandemic. For example, short-term home-based psychological interventions should be developed to reduce the negative effects of the second wave of COVID-19 pandemic on mental health.

The anxiety levels increased distress levels for those senior citizens who considered their information about the second wave of COVID-19 insufficient; had hyper-emotionality; longed for their families; and felt tense, overwhelmed and lonely during the pandemic. In addition, factors such as constraints of flexibilities, prevention of socialization and decreased physical movements also affect distress in senior citizens.

In spite of the fact that literature shows that big data analytics (BDA) pass on a distinct corporate ability, little is thought about their performance impacts, specifically logical conditions. Establishing this research in the dynamic capability view (DCV) and corporate culture and dependent on an sample of 310 Indian production industries, the purpose of this paper is to experimentally study the impacts of BDA on corporate social performance (CSP) and corporate green performance (CGP) using variance-based structural equation modeling (for example, PLS).

A questionnaire was used to accumulate data sets to examine research hypothesis. The authors pre-examined the survey with six scholastics and six directors from production firms in India. With the help of their sources of data, the authors have adjusted their wordings to improve the transparency and guarantee that length of the survey is accurate. Finally, the questionnaire was prepared for definite data collection.

The authors conclude that BDA has noteworthy effect on CSP/CGP. Notwithstanding, the authors did not find proof for directing role of flexible direction and control direction in the connections among BDA and CSP/CGP. This research offers a more nuanced comprehension of the performance ramifications of BDA, and in this way, it is tending to the critical inquiries of how and when BDA can improve in supply chains.

This investigation makes helpful commitments to the BDA research and its effect on CSP/CGP. To the authors’ best of information, this is the first hypothesis-focused approach to clarify the effect of BDA on ecological and social supportability. Second, this investigation likewise gives empirical proof that BDA impact on CSP/CGP and is free of flexible or control direction of the industry.

The purpose of this paper is to present a unique model for the production–recycling–reuse of aluminium refreshment cans. It is presumed that disposed-off 250-ml aluminium cans are collected from the retail outlet. The cans are thereafter arranged into non-tainted and tainted categories.

The current model considers all the factors, i.e. producing, recycling and remanufacturing, whereas the previous models provide emphasis only one factor. Six procedures were considered in the improvement of the mathematical model.

In this paper, a recycling–reuse model that remanufactures non-tainted aluminium beverage cans and uses regrind from damaged non-tainted aluminium beverage cans mixed with parent aluminium material in the production of new cans was developed and analysed to reduce the amount of aluminium beverage cans that are disposed off in a scrapyard. The model is assumed to have no shortcomings, and the different percentages regarding the classes of cans are taken to be deterministic.

The model incorporates several unique aspects, including accounting for the cost of land use and associated environmental damage through the calculation of a present value that is charged to the manufacturer.

This paper aims to examine the traditional business communities and family businesses of India, their emergence and sustained growth.

The authors analyze the role of business communities in family businesses of India and identify business communities that have still sustained and marked a global presence.

Business communities such as Marwaris have the knack for business activities and are leaders of family businesses in India today, who have sustained their past success and continue to create new histories. Other traditional business communities such as Parsis, Sindhis, Chettiars and Gujarati banias have not been able to sustain much. Possible reasons were switching to white-collar jobs, taking up diplomacy and other professions, inter caste marriages, international migration in search of business and Indian government policies.

This study provides a useful source of information for academics, policy-makers and economists.

Traditional business communities populate the list of family businesses that have marked their global presence. This paper identifies various factors that are responsible for the growth and sustainability of these business communities.

The study clarifies the role of business communities in domestic economic development.

The paper explored traditional business communities of India and assessed their role in family businesses of India that currently mark a global presence.

The paper aims to develop a novel method for the classification of different physical activities of a human being, using fabric sensors. This method focuses mainly on classifying the physical activity between normal action and violent attack on a victim and verifies its validity.

The system is realized as a protective jacket that can be worn by the subject. Stretch sensors, pressure sensors and a 9 degree of freedom accelerometer are strategically woven on the jacket. The jacket has an internal bus system made of conductive fabric that connects the sensors to the Flora chip, which acts as the data acquisition unit for the data generated. Different activities such as still, standing up, walking, twist-jump-turn, dancing and violent action are performed. The jacket in this study is worn by a healthy subject. The main phases which describe the activity recognition method undertaken in this study are the placement of sensors, pre-processing of data and deploying machine learning models for classification.

The effectiveness of the method was validated in a controlled environment. Certain challenges are also faced in building the experimental setup for the collection of data from the hardware. The most tedious challenge is to collect the data without noise and error, created by voltage fluctuations when stretched. The results show that the support vector machine classifier can classify different activities and is able to differentiate normal action and violent attacks with an accuracy of 98.8%, which is superior to other methods and algorithms.

This study leads to an understanding of human physical movement under violent activity. The results show that data compared with normal physical motion, which includes even a form of dance is quite different from the data collected during violent physical motion. This jacket construction with woven sensors can capture every dimension of the physical motion adding features to the data on which the machine learning model will be built.

Unlike other studies, where sensors are placed on isolated parts of the body, in this study, the fabric sensors are woven into the fabric itself to collect the data and to achieve maximum accuracy instead of using isolated wearable sensors. This method, together with a fabric pressure and stretch sensors, can provide key data and accurate feedback information when the victim is being attacked or is in a normal state of action.

A well-designed supply chain performance measurement system, should account for not only the capabilities and performance attributes of the focal firm but also its supply chain partners. The purpose of this paper is to help design a system that strikes a balance between the strategic objectives of the focal firm and its supply partners vis-à-vis the requirements of supply chain performance (cost, quality, speed and customer taste).

A theoretical framework on the strategic supply chain performance measurement system is developed based on existing literature and subsequently tested using a survey on 136 successful manufacturing organizations in India. The organizations were clustered into three strategy types and compared using analysis of variance on ranks to look for differences in preference for performance parameters.

The study examined the five dimensions of the supply chain practices, namely, strategic supply/distribution network, customer relationship, internal operations, information sharing and social and environmental responsiveness. The empirical results demonstrate the inclusion of business strategy orientation in designing today’s supply chain and hence its performance measurement system. Not supported hypotheses were addressed in the light of contextual factors.

The study is confined to finding preferences of non-financial aspects of supply chain performance and tier-1 suppliers. The research helps better design and benchmark supply chain performance metrics, based on the strategic choice of the firm.

This paper highlights the shortcomings in the existing performance measurement and gaps in the existing literature in the supply chain context. Further, it gives a holistic view of strategic supply chain performance measurement design.

The purpose of this paper is to provide an analysis on the relationship between information technology (IT) adoption and its usage and firm performance (banking and software firm) in India. Firm performance was measured with the help of three important variables: efficiency, effectiveness and productivity. Each one of the above has been described with a set of pretested questionnaires. Banks in India, in particular are geared for comprehensive banking solutions with extensive branch networks. Result from statistical analysis was validated with that achieved from ANN modeling.

Survey instrument was pilot tested. The pilot survey was administered to 20 randomly selected Indian service firms, whose Standard Industrial Classification codes were 6,021 (nationalized commercial Banks) and 7,371 (software firms). A 50 percent response rate was received. Internal reliability using Cronbach’s α was carried out for the entire set of responses from the pilot study. In addition, qualitative follow up from respondents was done. Unreliable items were deleted and modifications wherever necessary were made.

The research finds two important results with respect to IT adoption and firm performance. The first result is that service firms who implemented IT tools and techniques early achieved more turnover thereby greater market share from innovation/adoption (world-first and, to some extent India-first). These firms are able to better commercialize their service even if their most important innovations/adoptions supported by vendor’s to some extent. The second result is that service firms, which introduce new services, even if the service is already on the national or international front, derived more commercial sales from innovation, thus achieving more firm performance. Therefore, late followers (firm-first) would have higher sales from innovation by introducing services with high original content.

Performance is measured due to IT adoption.

Flowers and fruits of Madhuca longifolia (Koenig) (mahua) tree are edible and used as traditional Indian medicines. The physicochemical properties of different parts of mahua are investigated. This study aims to estimate the different mineral contents, polyphenols compounds and antioxidant activities by 2,2-diphenyl-1-picrylhydrazyl inhibition, reducing power, free radical scavenging activity using 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) and ferric reducing antioxidant power assays of mahua flower, ripe and unripe fruit.

Flavonoids were identified and quantified in yellow flowers and fruits of M. longifolia tree by high-performance liquid chromatography with diode array detector. Low molecular weight carbohydrates were determined by the ICBio scan, a specific method for determining of carbohydrates. Mineral content is determined by laser-induced breakdown spectroscopy (LIBS) and atomic absorption spectroscopy. Physicochemical, nutritional and mineral properties of mahua flower, ripe and unripe fruit were investigated by the statistical approach of principal component analysis (PCA).

Ascorbic acid, gallic acid (GA), quercetin and myrcetin were the phenolic compounds identified and quantified in mahua flower and fruit extracts. Sugar profiling of mahua flowers and fruits confirmed the presence of inositol, sorbitol, mannitol, dextrose, fructose, sucrose, raffinose and maltose. The mineral content of Na, K, Mg and Ca was present in quite a good amount in all samples. Total phenolic content (TPC) was significantly high in mahua flower (25.3 ± 1.0 mg GA equivalent/g FW) followed by mahua unripe (15.8 ± 1.0 mg GA equivalent/g FW) and ripe fruit (14.3 ± 1.0 mg GA equivalent/g FW) at p = 5%. In contrast, total flavonoid contents (TFCs) were highest in ripe fruit, then mahua flower and unripe fruit. Positive correlations were predicted by PCA for mahua flower with TPC, antioxidant activity assays and minerals except for Na; ripe fruit with TFC and Na; and unripe fruit with maltose and sorbitol.

This study demonstrates the application of LIBS for the determination of elements present in the mahua flowers and fruits and reveals that mahua can be a good source of nutrients. Sugar profiling of mahua flower showed that it is a rich source of reducing and non-reducing sugar, proving that mahua flower juice can be used as a natural sweetener in the development of different food products, namely, biscuits, cookies, cake, jam, jelly, juice and squash.