MEASI Institute of Management

Purpose Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC. Design/methodology/approach To examine the behavioural intention of employees in the retail SC, the research uses three theories – the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis. Findings This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector. Practical implications This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only. Originality/value This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC.

Marketing campaigns of organic food emphasize utilitarian benefits and psychological benefits as well as consumer culture to enhance environmental sustainability. In order to study the purchase intention of organic food, the authors developed a model using antecedents like warm glow, subjective norm, attitude and perceived behavioral control. This study examines the model for the Indian and the USA samples and thus integrated using three theories: Theory of Planned Behavior (TPB), Pro-Social Behavior (PSB) Theory with the interaction of Consumer Culture Theory. The model is estimated using the multi-group Partial Least Square Structural Equation Modeling (PLS-SEM) technique using R software with samples from India (n = 692) and the USA (n = 640). Results differ for Indian and USA samples. The expectation of the “warm glow” resulted from an environmentally friendly purchase as having a higher influence on Indian samples than that of the USA. Further, the attitude towards organic food purchase intention is stronger for US samples than the Indian, and the group difference is significant, while all the relationships that take warm glow as an antecedent have higher β for Indian samples. Moreover, the study found that attitude towards organic food is a major element for US subsamples, whereas subjective norm plays a major role in Indian samples to adopt organic food. Managerially, the present study suggests that a firm marketing its organic food must concentrate more on “warm glow” for Indian consumers in order to improve their market share.

Purpose Paradoxical leadership (PL) is a style that can bring stability and flexibility simultaneously, which helps organizations to manage the uncertain external environment. The purpose of this study is to identify if PL could moderate the relationship between organizational silence and employee voice. Design/methodology/approach Data for the study were collected from a sample of 617 gainfully employed factory employees using three standardized questionnaires. The data were analyzed using structural equation modelling (SEM) through Python programming. SEM was used to test the mediating, moderating, and serial-parallel relationship of the proposed model. Findings The research study found that organizational inertia led to silence among employees. It was also found that PL moderated the relationship between organizational silence and employee voice. Originality/value A fair review of the literature showed that studies that examine the effect of PL on organizational silence are scarce. The present study is a modest effort towards addressing this gap in the literature. The findings of the study are significant and have made a substantial contribution to management literature.

Abstract Advertising in India from the 1980s until very recently has portrayed women as having sole responsibility for housework, even when they are employed. Women have been expected to live with restrictions imposed by men. In the last decade, the culture has begun to acknowledge women’s rights in limited ways, in part because of rising living standards. As a result, some cutting‐edge advertisements have begun to present a wider range of roles available to women. This article examines 10 Indian TV commercials and their relation to cultural attitudes about women and their role in society. The new advertisements recognize the need for gender equality, although they still express that ideal in relatively conservative terms.

Purpose The present study aimed to evaluate the psychometric properties of the short form of personal optimism and self-efficacy optimism-extended (POSO-E) among Indian teachers. Design/methodology/approach Two studies were conducted to adjudge the reliability and validity of the scale. In the first study, the sample of 510 respondents was randomly divided into subsamples. The first subsample was subjected to the Exploratory Factor Analysis which yielded a two-factor solution explaining 71.02% of the variance. This model was subjected to the Confirmatory Factor Analysis using a second subsample. Acceptable model fit indices suggested factorial validity of the two-dimensional POSO-E among Indian teachers. In the second study, acceptable Cronbach's alpha and composite reliability estimates (greater than 0.70) indicated the scale's reliability. Also, as expected, personal optimism, self-efficacy optimism and overall optimism reported a positive correlation with spiritual well-being and a negative association with distress. It confirmed the criterion validity of the POSO-E among Indian teachers. Findings The results showed appreciable psychometric properties of the POSO-E in the context of Indian teachers. The study offered a valid and reliable scale to measure teachers' optimism levels. It is poised to generate renewed interest among scholars to emphasize teachers' positive and optimist thinking. The findings also reported a positive association between teachers' optimism and spiritual well-being. It suggests that spiritual practices and interventions could be used to develop an optimistic academic workforce. Originality/value The study is one of the pioneer studies that evaluated the reliability and validity of the POSO-E among Indian teachers.

Purpose This paper aims to examine the influence of environmental concerns and consumers’ knowledge of green brands on their purchasing decisions of green products, utilising green trust as a mediator. Design/methodology/approach Responses from 383 Indian consumers were collected, which was analysed using descriptive and inferential statistics. The causal relationships between latent variables and mediating effect of green trust were investigated by performing Structural Equation modelling. Findings Green trust served as a crucial factor in mediating the relationship between environmental concern and green purchase decision. Trust in eco-friendly products significantly influenced the consumers’ decisions to make green purchases. The study further validated that environmental concern significantly influences individuals’ decisions to make green purchases. Research limitations/implications The study employed a cross-sectional research design to elucidate the relationship among the factors. However, a longitudinal research design is recommended for further study to ascertain the actual purchase decision and evaluate the reliability of the results. Practical implications Marketers can use the study findings to understand consumer knowledge better and trust in green and sustainable products. The proposed model will support marketers and policymakers in developing appropriate marketing strategies as well as facilitate educating consumers about the nuances of green products and the habit of buying eco-friendly products. Originality/value Study’s novel contribution is mediation between environmental concern and green purchase decision through green trust.

Purpose The main purpose of this research is to investigate the influence of promotional inputs presented to salespeople, such as continuing medical education (CME) sponsorship and drug samples, on adaptive selling and sales performance. Design/methodology/approach This study used a mixed-methods approach. First, depth interviews were done and this was followed by a survey on 247 pharmaceutical executives in India. Data analysis was done using AMOS, Process Macro and floodlight analysis. Findings Results showed that CME sponsorship and drug samples drove adaptive selling and sales performance positively. Additionally, results reveal that CME program sponsorship negatively moderated the adaptive selling–sales performance relationship; free drug samples too negatively moderated this relationship. Practical implications Firms may hire salespersons with high customer orientation and adaptive selling and train them hone these further. The present research also crucially suggests that pharma firms may allocate CME sponsorship and drug samples to salespeople low on adaptive selling. Originality/value This could be the first study, to the best of the authors’ knowledge, that uses promotional inputs (such as CME sponsorship and drug samples) as an antecedent to adaptive selling and sales performance. Moreover, this is the only research that has tested CME sponsorships and drug samples as moderators to customer orientation–adaptive selling and adaptive selling–sales performance.

The concept of employee welfare is vibrant. Its broad viewpoint and contents are inclined to change, depending on social and economic changes that occur in society. Employee welfare includes various services, benefits, and facilities offered to employees by employers. An organization has to provide welfare facilities to their employees to keep their motivation levels high. The study throws light on impact of welfare measures on the employees’ performances with respect to the construction industry. The primary data for the study was collected through a questionnaire. The sample size of the study was 80 and the sample design adopted was a systematic random sampling technique.

Objectives: The study explored the dimensions of antecedents of abuse, such as physical abuse, sexual abuse, neglect, and emotional abuse, which leads to the consequences of child abuse. The data were examined for model fitness towards the causes and effects of child abuse. Methods: The research underwent an empirical study analysing and testing through a structured questionnaire, and the purposive sampling technique was adopted. As many as 500 questionnaires were dispersed among children in various government schools in OMR, Chennai, Kanchipuram district, and finally 325 questionnaires were considered to be usable for analysis. The survey was conducted in the year 2016; the study data were collected over a period of 3 months. The participants chosen for the study were in the age group of 11 to 17 years and were students from high schools and higher secondary schools. The final sample consisted of 325 students. The schools where the participants studied catered mainly to families who belong to lower-middle socioeconomic class. The questionnaire was structured in such a way to elicit demographic details and determine variables to pose questions through different formats, such as Likert Scale, dichotomous questions, and rating scale questions. The secondary data used in our study were gathered from the reports of the primary health care centres functioning near the schools covered in our study. Findings/ application: Reliability of the items in the questionnaire was above 0.65, and on final consolidation, Multiple Regressions and SEM were used to test the hypotheses; statistical analysis was carried out using software such as SPSS 2.0 and AMOS 2.1. Stepwise multiple regression analysis was performed, taking Physical Abuse, Sexual Abuse, and Neglect and Emotional Abuse as the independent variables and Child Abuse as the dependent variable. All the dimensions of antecedents emerged as significant predictors to child abuse. The collinearity statistics revealed the absence of multicollinearity between independent variables. As for relative importance of each variable, physical abuse (0.71), sexual abuse (0.88), neglect (0.83), and emotional abuse (0.75) made the strongest contribution in exploring the dependent variable. This resulted in the rejection of null hypothesis. Multiple determination factor R2 (Goodness of fit) value was 0.39, and F value of the regression, 79.87 (p < 0.01). Factor R of multiple cross-correlations showed high cross-correlation, which is less than the acceptable level of 0.01; the results of CFA suggest that the factor loadings for all major variables range between 0.89 and 0.98. SEM was performed to test the goodness of fit using large sample size, and the following values were obtained: Goodness of fit (GFI) indices = 0.98, AGFI = 0.90, CMIN = 77.8, PGFI = 0.37, RMSEA = 0.07, CFI = 0.999, GFI = 0.99, and IFI = 0.99.Keywords: Child Abuse, Antecedents, Consequences, Physical, Emotional, Sexual Abuse

The service sector in India has been growing rapidly, and its contribution to Gross Domestic Product (GDP) is increasing year after year. In the service sector, financial service is the lifeblood of economic activity, and in the financial service, banking plays an increasingly important role in the economy of a nation. At present, the focus of banks is on the customer. The number of players being large, customers have a good range of choice. Customer usually picks up a bank which provides maximum satisfaction and quality service. This has led banks to adopt more customer-oriented policies and schemes aimed not only to increase the number of customers but also to retain the existing customers. So, an attempt has been made by the researcher to study the demographic variables that influence the service quality in banking. The study was undertaken only in the private sector banks of Chennai. The sample size of the study was 300. Both primary and secondary data were used for the study. The primary data collected for the study were analyzed with the help of SPSS package by using ANOVA. The findings of the study help to know which demographic variable influences the service quality of banks. This information also helps the banks to understand their customers better and improve their service quality in order to enhance customer satisfaction.

The banking industry needs to set up strong detection systems to fight the continuing risk of fraud in order to keep people’s trust in financial systems and keep their cash safe. Problems often arise with traditional rule-based detection systems when they are put up against complicated fraud plans. It is possible to find fake activities more easily now that machine learning and big data analytics are becoming more popular. In this research, a complete approach is introduced that makes it easier to spot fraud in banking systems. The system has algorithms for machine learning, important management parts, and big data analytics. using “big data” technologies to collect and examine a lot of data from a lot of different sources, such as external data streams, internal transaction records, and profiles of customers. Fraud detection systems get better at telling the difference by picking out key features from preprocessed data. Researching on a system that will constantly watch all incoming transfers and send alerts right away if any suspicious activity is seen. Because of this, it is necessary to set limits, create automatic systems for sending out warnings, and come up with ways to spot anomalies. The financial industry must make sure that the methods they use to find and stop fraud are legal and meet their compliance responsibilities.

The Learning Management System (LMS) is a type of online software application or web-based technology used to plan, implement and assess a specific learning process.The use of LMS technology is growing rapidly in higher education, particularly in the areas of distance learning, blended learning and flipped classrooms.This paper presents a systematic literature review of the existing research on the effectiveness of LMS in improving student learning.The objectives of this systematic literature review are to: Identify the existing research on the effectiveness of LMS in improving student learning outcomes.Examine the effects of LMS on student engagement and satisfaction.Analyze the factors that influence the effectiveness of LMS in improving student learning.The review focused on studies that have examined the effects of LMS on student learning outcomes, engagement and satisfaction.This systematic literature review was conducted using a combination of search strategies.The search was conducted using the databases Google Scholar, Web of Science and Scopus.The keywords used in the search were "Learning Management System", "Student Learning", "Effectiveness" and "Systematic Literature Review".The search was limited to peer-reviewed articles published within the last 10 years (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016).The literature review revealed that an LMS can be beneficial in improving student learning outcomes and increasing student engagement and satisfaction.However, the findings were not consistent, and the effects of LMS on student learning depend on several factors, including the type of instruction, the type of LMS and the level of student engagement.

Maintaining a competitive advantage over their respective rivals depends on companies giving PADS (Predictive Analytics and Decision Support Systems) top priority. Conversely, experts in human resources often find it difficult to predict, from the current data, the expectations of employees. This work targets an original PADSS idea, Deep Decision Tree (DDT), with an aim of extracting already existing data. The authors of this work used the DDT method since it is efficient in handling big datasets. By means of an analysis of a range of data including publicly employed individuals, companies, and products that make use of technology, this paper aims to show how DDT could be able to better fulfill the employment requirements of the future. When compared to other approaches regarded to be quite conventional, the DDT method provides better accuracy and scalability. Professionals in the field of human resources can then use this data to make well-informed decisions about the configuration of digital workforce. This work significantly advances the field by laying a fresh basis for PADSS by means of advanced machine learning techniques.

In the different points of the decision making proccess, a buyer who uses more than one channel is referred as multi-channel customer. Then, a buyer who includes only single choice in his shopping process is referred as single channel buyer. This study analyzed channel choice conduct utilizing a Theory of Planned Behavior by impacts in community pharmacy, e-Pharmacy, and Multi-channel. Also, it recommends omnichannel strategies for community pharmacies A self-regulated questionnaire was utilized (N = 426) to understand consumer channel choice across the channels. The initial step of the two-stage analysis comprises of the evaluation of the outer model. A confirmatory factor analysis (CFA) was used to test the underlying structural Equation model. The CFA was completed using the SmartPLS 3. The evaluation showed that the TPB was significant and found subjective norms was effective across the channels. The distinction between single and multichannel is explained with the context to community pharmacy, e-Pharmacy, and Multi-channel. This Study sets the ground for collaborates in the medical services and Pharmaceuticals to improve their understanding of what drives to purchase in different channels. Furnished with this information, advertisers and healthcare experts could design and execute their promoting methodology more effectively.

In today's rapidly evolving business landscape, the emergence of disruptive technologies and innovative business models have revolutionized traditional market structures. One such transformation is the shift towards decentralized marketplaces, driven by blockchain technology, smart contracts, and decentralized finance (DeFi) solutions. This chapter aims to explore the concept of disruptive business models and their profound impact on market dynamics, focusing on the rise of decentralized marketplace. This chapter addresses a pressing need for comprehensive, up-to-date, and insightful information on a topic that is rapidly changing the business landscape. It provides a valuable resource for a diverse audience, ranging from industry professionals to academics and policymakers. It can be highly beneficial for several reasons, given the ongoing evolution and significance of decentralized marketplaces.

The Internet of Things is becoming mainstream in all computer science fields. In the near future, the Internet of Things (IoT) will affect the economy, enterprises, and society. However, the cross-cutting nature of transdisciplinary components and IoT systems utilized in such projects has revealed new security concerns. Nodes in an Internet of Things network generally lack resources, making them ideal targets for hackers. Internet of Things devices have basic security weaknesses, therefore authentication, encryption, application security, and access networks are worthless. This architecture uses NFV and SDN enablers to mitigate system vulnerabilities. This artificial intelligence framework uses anomaly-based models to detect IoT system intrusions and network trends using a monitoring agent and an AI-based response agent. ML approaches are needed to change IoT system protection from secure communication to intelligent security solutions. Test results prove the recommended strategy can work. Data mining may be a cost-effective strategy to find high-performance attacks. Specifically, this may detect attacks. This is because it emphasizes dispersion data. We used a single-class support vector machine to test our anomaly-based IDS for the Internet of Things. A real intelligent building environment was used for the assessment. Abnormalities were correctly identified 99.71 percent of the time. An idea’s practicability is investigated to find existing answers and encourage study into unsolved challenges.

This study's objective is to examine waste management systems for the food sector, to identify longer lasting and circular processes. In a particular case study, a food industry waste management system was assessed and improved. To collect information and data from Lean Six Sigma, the DMAIC (Define – Measure – Analysis – Improved – Control) Model was employed. A carbon footprint was calculated to determine the waste management system's sustainable development and to compare the consequences of various CO2 waste disposal technologies for each category. The food business makes a sizable contribution to waste production in a consumer society. Food businesses are critical in addressing resource efficiency and waste prevention concerns. The circular economy and retail have begun to take this path as a significant alternative to the standard business paradigm. In the food business, a new waste management system has been implemented that has demonstrated enhanced performance. Our comparison of various waste treatment methods, particularly in the circular economy, emphasizes the importance of recycling. We then concentrated on organic material and compared their composability and anaerobic digestion to the category of garbage. Anaerobic digestion has been shown to reduce greenhouse gas emissions. Other food businesses can manage similar improvement programs directly without duplicating the analysis. Future study on biogas and other organic waste by products will benefit from our findings. Lean Six Sigma and other environmental technologies could be integrated into the circular economy.

In the line of Fintech and Infotech, now “Agritech” is the most pronounced jargon in our country. Being an agricultural country, India started incorporating technology into the agriculture sector. The population of the world is estimated to reach 9.7 billion in the year 2050 and the existing resources for food production might not be sufficient to meet the needs which are expected to increase exponentially in the years to come. To cater to the needs of the country, Agri tech is needed. Blockchain, IoT, Drone-based farming and other data-driven technologies are enabling agriculture to evolve into a technological industry and making the farmer’s task easy. In this research paper, the researchers comprehensively visualized the Agritech related papers in the bibliometric method from the Scopus database for the years 1987 to 2022. The outcome of the paper is to develop the technology in agriculture even better than now and build a nationwide farmer network for food security. This research study has identified a research gap which is to integrate agri business and agri tech together for creating a value chain in the sector.

Corporate hypocrisy (CH), organizational inertia (OI), and silence are undoubtedly issues many organizations have faced recently. Effective management of these paradoxes requires a different type of leadership. Based on the Paradox theory, Information Manipulation theory, and a few other related theories, the authors propose paradoxical leadership (PL) as an ideal style to deal with such situations in the current volatile and uncertain business environment. The study examined whether PL can revert silence induced by CH and OI to make employees air their voices and facilitate good performance. Data for the study was collected from 617 (response rate of 88.14%) gainfully employed samples. The data was analyzed using Structural Equation Modeling (SEM). Results show that PL can moderate the relationship between employee silence induced by CH and OI and facilitate voice behavior. The study also presented a few plausible suggestions that organizations could adopt to deal with silence and induce voice. The study is expected to stimulate heightened research interest in the fecund area.

Stability among healthcare professionals is considered critical to providing excellent care. Job satisfaction has a significant impact on the productivity and efficiency of human resources in the healthcare industry. This cross-sectional study examined the job satisfaction and retention intentions of healthcare professionals in primary healthcare centers in Tamil Nadu. Convenience sampling was used to collect data from 334 respondents using a validated structured questionnaire. The empirical research revealed that their work values were the most significant predictor of job satisfaction among PHC employees. On the other hand, time pressure had the least significant relationship with PHC employee satisfaction. The findings indicate that targeted interventions to enhance health workers' job satisfaction, reduce stress, and increase positive work values are essential to creating a positive work environment and increasing job satisfaction. This study adds to the literature on job satisfaction and retention of primary healthcare workers in Tamil Nadu. We recommend that healthcare managers promote and enforce PHC workers' work values to keep them positive. Work values and PHC workers' satisfaction and intention to stay have received little research attention. One of the first studies to empirically examine quality improvement, time pressure, commitment, compensation, and work values as dimensions of job satisfaction among health professionals in Tamil Nadu Primary Health Care Centers.