Consumer Expectations on Supermarkets in Organized Retailing

The study emphasise on the consumer expectations on supermarkets in organised retailing and factors which acts as driving force for consumers to opt for the same, with reference to Chennai city. The sample size is 120 respondents who were retail customers of Supermarkets under Non- Probability Judgment Sampling method. The growth of Supermarkets of India in recent years has been witnessed due to increased consumer expectations. As most of the retail segments try to find their way to come out of the COVID-19 pandemic, it must be noticed that the consumers are already evolving at great speed in their expectations in all fields. At the pandemic situations, people try to venture out most importantly for essential items with the available outlets, taking care of all safety measures. The immediate next option available for consumers is online shopping. The blowout of virus has not only changed the way how consumers shop, but also their buyer behaviour pattern and what they actually expect from retailers. By 2025, India is expected to become the world’s third largest economy as it is experiencing the world’s fastest growing economies. According to various reports, it is known that these new spending and shopping patterns is expected to continue even after the crisis comes down. With more developments as well as challenges in the field of organized retailing, consumer preferences are changing from region to region.

Perceptions Underlying Addictive Technology Use Patterns: Insights for Cognitive-Behavioural Therapy

Cognitive-Behavioural Therapy (CBT) is considered the ‘gold standard’ in the treatment of addictive disorders related to excessive technology use. However, the cognitive components of problematic internet use are not yet well-known. The aim of the present study was to explore the cognitive components, that according to problematic users, can lead to potential internet addiction. A total of 854 European adults completed an online survey using a mixed-methods design. Internet problems and attachment styles were assessed, prevalence rates estimated, correlations, chi-squared automatic interaction detection, and content analysis were performed. Self-reported addictions to social networking, internet, and gaming had a prevalence between 1.2% (gaming) to 2.7% (social networking). Self-perception of the addiction problem and preoccupied attachment style were discriminative factors for internet addiction. In an analysis of qualitative responses from self-identified compulsive internet users, a sense of not belonging and feeling of disconnection during life events were perceived as causes for internet addiction. The development depended on a cycle of mixed feelings associated with negative thoughts, compensated by a positive online identity. The severity of this behaviour pattern produced significant impairment in various areas of the participants’ functioning, suggesting a possible addiction problem. It is suggested that health professionals administering CBT should target unhealthy preoccupations and monitor mixed feelings and thoughts related to internet use to support coping with cognitive distortions.

An Empirical Study of the Indian IT Sector on Typologies of Workaholism as Predictors of HR Crisis

Workaholism, in recent years, has become a regular behaviour pattern among professionals. While self-negligence is assumed as a hallmark of workaholism, empirical data in this case stands to be both narrow and paradoxical. Modern developments like high-speed data connections add more to this belief, as this makes it possible for employees who would like to work at any place and at any given point of time to work. Workaholism is found to affect several important domains of life. With regards to work domain, workaholics commonly seem to have poor associations with their peer/colleagues, most likely on the grounds that they often feel the need to control them and experience issues with delegating work. Given that the amount of time they invested in their work leaves little energy for them for other activities, also the social life outside work gets hampered. This chapter explores the relationship between workaholism, perceived work-related stress, different job conditions, and intensifying anxiety among IT professionals in Delhi/NCR.

Artificial intelligence: a systematic review of methods and applications in hospitality and tourism

Purpose Several review articles have been published within the Artificial Intelligence (AI) literature that have explored a range of applications within the tourism and hospitality sectors. However, how efficiently the applied AI methods and algorithms have performed with respect to the type of applications and the multimodal sets of data domains have not yet been reviewed. Therefore, this paper aims to review and analyse the established AI methods in hospitality/tourism, ranging from data modelling for demand forecasting, tourism destination and behaviour pattern to enhanced customer service and experience. Design/methodology/approach The approach was to systematically review the relationship between AI methods and hospitality/tourism through a comprehensive literature review of papers published between 2010 and 2021. In total, 146 articles were identified and then critically analysed through content analysis into themes, including “AI methods” and “AI applications”. Findings The review discovered new knowledge in identifying AI methods concerning the settings and available multimodal data sets in hospitality and tourism. Moreover, AI applications fostering the tourism/hospitality industries were identified. It also proposes novel personalised AI modelling development for smart tourism platforms to precisely predict tourism choice behaviour patterns. Practical implications This review paper offers researchers and practitioners a broad understanding of the proper selection of AI methods that can potentially improve decision-making and decision-support in the tourism/hospitality industries. Originality/value This paper contributes to the tourism/hospitality literature with an interdisciplinary approach that reflects on theoretical/practical developments for data collection, data analysis and data modelling using AI-driven technology.

A REVIEW STUDY ON UNDERSTANDING GRIEF: ATTACHMENT, LOVE AND LOSS

There is a reason why the phrases "love and loss" appear so frequently in mourning literature. Love and loss are two sides of the same coin; when we choose one, we open the door to the possibility of the other (Kosminsky & Jordan, 2016, p. 53). It is hardly surprising, therefore, that some similarities arise in how we establish attachment relationships and react to them throughout detachment and reattachment. Each person we love is unique, regardless of how many close relationships we have or with whom we have them. As a result, mourning for that person is a oneof-a-kind experience when the time comes. However, these universal sentiments share certain characteristics, which provide a framework for comprehending loss (Shear In Neimeyer, 2016, p. 14). Loss is an inevitable part of life and development. This may sound paradoxical, but the truth is that new life, change, and forward progress can only occur through losing (changing) an old lifestyle, behaviour pattern, or other aspects of the status quo (Walter & McCoyd, 2009, p. 1). Grief and mourning are the terms we hear the most in the current condition of transition to the new normal during Covid-19 circumstances, whether it is the loss of a person or an object. Recognising necessity, the authors endeavoured to conduct a review study on grief and associated concepts such as attachment, love, loss, mourning and bereavement from various perspectives. Finally, a personal experience is shared to make the study more impactful. By breaking the notion down into its core components, the current study provides everyone interested in exploring grief with a methodical overview as well as a rm understanding of the concept. Those seeking further information in the original literature will nd detailed references included.

Results of Cluster Analysis of Semantic Features “What is the Person’s Gender? and “What is the Person’s Appearance?” for the Stimulus “Flirting Person””

The present work continues a series of studies concerning ludic competence/ playfulness by means of psycholinguistic instruments and is devoted to description of the behaviour pattern of the ludic position “Diplomat”, which corresponds to flirting as one of the components of playfulness. The key research method is psycholinguistic experiment whose main stage is the controlled association experiment (CAE) with the stimulus “flirting person”. The sample consisted of 215 young respondents (age 21-35). The instructions for the controlled association experiment was developed in the frame of the parametric concept of I.A. Sternin. 23 questions (semantic features) were formulated. They were recognized as relevant to communication for the stimulus “flirting person” and allowed to obtain the material for describing the behaviour pattern of ludic position Diplomat (“flirting person”) reflecting the reality of linguistic consciousness of native speakers. This study presents the results of cluster analysis of two association fields built for the following semantic features: “What is the person’s gender?” and “What is the person’s appearance?”. The results of cluster analysis of the association field built for the semantic feature “What is the person’s gender?” indicate that in the linguistic consciousness of the inhabitants of Ukraine, the overwhelming majority of respondents (93%) accept the binary concept of gender, for 3% of respondents gender does not matter, and only one respondent considers the transgender identity. The analysis of the association field built for the semantic feature “What is the person’s appearance?” allows us to assert that the absolute majority of respondents (78%) demonstrates an emotionally positive attitude towards “flirting person”.

Ameliorative effect of Acetyl L-carnitine in Alzheimer's Disease via Downregulating of Homocysteine Levels in Hyperhomocysteinemia Induced Cognitive Deficit in mouse model

Aim: The study was aimed at exploring the role of Acetyl L-Carnitine supplementation attenuating dementia and degradation of cognitive abilities in Hyperhomocysteinemia induced AD manifestations in the mouse model. Background: Alzheimer’s disease (AD) is a neurological disorder that is marked by dementia, and degradation of cognitive abilities. There is great popularity gained by natural supplements as the treatment for AD, due to the higher toxicities of synthetic drugs. Hyperhomocysteinemia causes excitotoxicity to the cortical neurons, which brought us to the point that amino acids possibly have a role in causing cholinergic deformities, which are an important etiological parameter in AD. Acetyl L-Carnitine a methyl donor with the presence of three chemically reactive methyl groups linked to a nitrogen atom was found to possess neuroprotective activity against experimental models of AD. Objective: The objective of the present investigation was to investigate and evaluate the pharmacological effect of Acetyl L-Carnitine against hyperhomocysteinemia induced Alzheimer’s disease (AD) in the mouse model. Material and Method: The animals were divided into normal control (vehicle-treated), HHcy (dl-Homocysteine thiolactone treated) negative control, test group i.e., low dose (50mg/kg, p.o) of acetyl L-carnitine (L-ALC), high dose (100mg/kg,p.o) of acetyl L-carnitine (H-ALC), L-ALC+SOV (Sodium orthovanadate) and H-ALC+SOV. HHcy was induced by administration of dl-Homocysteine thiolactone (dl-HCT; 1 g/kg, p.o.) on day-1 to day-15 of experimental schedule to all animals except normal control. The changes in the behaviour pattern of the animals due to neuroinflammation, and cholinergic dysfunction were examined in rotarod, novel objective recognition, passive avoidance, elevated plus maze, and morris water maze analysis. Biochemical investigation includes the estimation of total homocysteine (tHcy), Creatinine Kinase (CK), Acetylcholinesterase (AChE), thiobarbituric acid reactive substances (TBARS), reduced glutathione (GSH) and IL-6 and TNF-α. Result: Supplementation of ALC in mouse considerably lowered the HHcy-induced AD manifestations in the experimental animals. It was found that ALC and SOV successfully diminished the behaviour abnormalities and lessened the Hcy-induced alteration in systemic Hcy levels, CK activity, and cholinergic dysfunction with improved bioenergetics in the Prefrontal cortex of the mice. Conclusion: ALC was found to improve the HHcy-induced cognitive disabilities which was found to be associated with the decreased systemic levels of Hcy, CK, and cholinergic abnormalities. It also combats the oxidative stress-induced neuroinflammation with diminished pro-inflammatory markers in the pre frontal cortex. The outcomes collectively indicate ALC's potential to be used as a supplementation in the pharmacotherapy of AD.

Analysis of mergers and acquisitions between 2009 and 2020

This paper studies the dynamics and trends in processes of mergers and acquisitions in a highly competitive and global economic environment. The aim of this study is to analyse and divide into periods M&A agreements in the global economy. The study produces a precise definition and discusses benefits and drawbacks of such horizontal and vertical agreements. The authors discuss historical waves of mergers and acquisitions processes and present 11 individual periods containing special aspects and description of types of the agreements, as well as supplement the periods with COVID-19 pandemic flow for 2020-2021. A polynomial regression analysis is used to predict the mechanism, results and magnitude of mergers and acquisitions. Furthermore, a discrete time model enables studying behaviour pattern of mergers and acquisitions happened during 2009-2020. The results demonstrate that transnational companies are greatly attributed to economic growth through mergers and acquisitions despite their rather high preparation and implementation costs. It may be expected an escalation of capital redistribution among pharmaceutical and bioengineering companies in a post-pandemic period due to increased M&A agreements.

Data Mining of Students’ Consumption Behaviour Pattern Based on Self-Attention Graph Neural Network

Performance prediction is of significant importance. Previous mining of behaviour data was limited to machine learning models. Corresponding research has not made good use of the information of spatial location changes over time, in addition to discriminative students’ behavioural patterns and tendentious behaviour. Thus, we establish students’ behaviour networks, combine temporal and spatial information to mine behavioural patterns of academic performance discrimination, and predict student’s performance. Firstly, we put forward some principles to build graphs with a topological structure based on consumption data; secondly, we propose an improved self-attention mechanism model; thirdly, we perform classification tasks related to academic performance, and determine discriminative learning and life behaviour sequence patterns. Results showed that the accuracy of the two-category classification reached 84.86% and that of the three-category classification reached 79.43%. In addition, students with good academic performance were observed to study in the classroom or library after dinner and lunch. Apart from returning to the dormitory in the evening, they tended to stay focused in the library and other learning venues during the day. Lastly, different nodes have different contributions to the prediction, thereby providing an approach for feature selection. Our research findings provide a method to grasp students’ campus traces.