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Financial integration being an increasingly important part of ongoing trade liberalization requires an in-depth analysis. This study seeks to survey all the available studies that try to measure the magnitude of cross-country integration. We see that primarily there are two types of measure available, viz De jure and De facto. These measures can be further broken down into different subparts which lay emphasis on different aspects of financial integration. We see that there is no accepted single universal index to measure financial integration, each actually having its own pros and cons and it is upon the researcher to use one or more that best fit his/her purpose.

Diabetes mellitus has become a major world health problem that has unenviable impacts on health of the people including quality of life (QOL) also and in which person’s physical and psychological state, social commitments and relationships and his interaction with the environment is affected. This shows that there is an urgent need for behavior change and considerable educational strategies for proper management and rehabilitation (Reddy, 2000). This research has identified and ranked the significant factors which affect the QOL in diabetic patients in India. The paper aims to discuss these issues.

In this paper, nine factors which affect the QOL in diabetic patients in India have been identified through review of the literature and evaluated by total interpretive structural modeling (TISM) approach, i.e. an extended version of ISM. In this approach, interpretations of the interrelationship among factors have been discussed. Therefore, TISM approach has been used to develop the model and the mutual interactions among these factors.

The results of the model and MICMAC analysis indicate that diet restriction, body pain and satisfaction with treatment are the top-level factors.

Identification of the factors that have a remarkable effect on the QOL in diabetic patients is very important so that the doctors and other healthcare professionals may handle these factors efficiently and proper rehabilitation can be provided to such patients.

This paper has used an application of the TISM approach to interpret the mutual relationship by using the tool of interpretive matrix and has developed a framework to calculate the drive and the dependence power of factors using MICMAC analysis. The issues related to QOL are extremely important, as they can strongly anticipate a person’s capability to govern his lifestyle with disease like diabetes mellitus and maintain good health in the long run. This shows the urgent requirement of an optimized model which can predict and interpret the relationships among these factors. In this research, the interrelationships among these factors have been developed and interpretations of these interactions have been given to develop a comprehensive model so that QOL of diabetic patients may be improved.

The vision of Industry 4.0 concept is to create smart factories that will change the current processes of production and manufacturing system using smart machines to produce smart and intelligent products. The main aim of this research is to explore the enablers with regard to Industry 4.0 application in manufacturing industry in India as the available literature shows that manufacturing sector is still doubtful about the implementation of Industry 4.0.

Seventeen enablers that can affect the adoption of Industry 4.0 in the manufacturing industry in India have been explored through an extensive review of available literature and viewpoints of industry and academic experts. Total Interpretive Structural Modelling methodology (TISM) has been used to evaluate the interrelationships among these factors. A TISM model has been developed to extract the key enablers influencing Industry 4.0 adoption.

The result shows that Internet facility from government at reduced price, financial support and continued specialized skills training are the major enablers as they have strong driving power.

Proper understanding of these enablers will help the managers and policymakers to explore the impact of each enabler on other enablers as well as the degree of relationships among them and to take concrete steps so that Industry 4.0 can be implemented successfully in the manufacturing sector in India.

This study is pioneer in exploring the enablers Industry 4.0 which is the most advanced concept that has the capability to change the future of Indian manufacturing sector if implemented judiciously and cautiously.

Lean concept is implemented in healthcare organizations, as it deals with improvement processes so that best services may be provided to the patients and competitive advantage may be achieved. The purpose of this paper is to evaluate the important factors which influence implementation of lean principles in the healthcare industry.

The factors influencing lean implementation in the healthcare industry have been determined through literature review and results of a survey where questionnaires were distributed among 325 healthcare professionals. Fuzzy Interpretive Structural Modeling (FISM) approach has been used to analyze the interrelationships among these factors. A FISM model has been developed to extract the key factors influencing lean implementation.

Results of the survey and model show that lean leadership, professional organizational culture and teamwork and interdepartmental cooperation are the top level factors. Clarity of organizational vision, communication of goals and results, follow up and evaluations are the factors with strong driving as well as strong dependence power. Even a slight action taken on these factors will have a significant impact on other factors.

The healthcare professionals and managers can acquire information from the drive power dependence matrix so that they can thoroughly understand the relative importance, interdependencies and relationships among these factors. The model will help in determining the hierarchy of various actions and activities which may be taken by the management for managing the factors that remarkably affect the lean management in hospitals.

In this paper, only 15 variables appropriate for the Indian healthcare industry have been identified. The model developed in the present research has not been validated statistically which can be done by structural equation modeling (SEM).

Though there are various studies which depict that lean principles have been implemented successfully in various industries, there are few studies specifying the application of lean principles in healthcare sector in India. This paper is an attempt to identify various factors which are important for application of Lean concept in the healthcare sector.

The purpose of this paper is to analyze the content of mission statements of India’s Super 50 companies, selected from Forbes India magazine, on multiple aspects such as components, stakeholders’ inclusion, content readability and strategic orientation.

A total sample of 29 companies was chosen for the study, whose mission statement details were available on their official websites. These firms’ mission statement was rated on the basis of nine selected components of what constitutes a “good mission statement.” Further, industry-level analysis was also carried out to measure significant differences between manufacturing and service industries. Data were analyzed using frequency analysis, average and t-statistics. Gunning Fog index was also calculated to measure content readability.

The results show that Indian firms largely focus on their customers as major stakeholders while defining their mission and emphasize upon values and philosophy, products or services offered, and integration of technology in production or processes. There is no statistically significant difference identified between the average mean value of components for sample manufacturing and service firms.

The study is cross-sectional in nature; however, a few firms redesign their mission according to need; therefore, a detailed longitudinal study of a few firms could open up new paradigms. The findings are based on sample firms selected from Forbes India, so generalization needs to be done with complete caution.

The study looks ahead of the most popular of David’s (1989) nine crucial components of mission statements, taking into account major shifts in the business environment. It also attempts to fill a contextual research gap by analyzing the mission statements of top Indian firms. Three crucial elements – “strategic decision,” “stakeholder concerns” and “critical success factors” – have been identified for Indian firms that define their mission statement.

The purpose of this paper is to evaluate the interplay of various measures used by different governments around the world in combatting COVID-19.

The research uses the interpretative structural modelling (ISM) for assessing the powerful measures amongst the recognized ones, whereas to establish the cause-and-effect relations amongst the variables, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used. Both approaches utilized in the study aid in the comprehension of the relationship amongst the assessed measures.

According to the ISM model, international support measures have the most important role in reducing the risk of COVID-19. There has also been a suggestion of a relationship between economic and risk measures. Surprisingly, no linkage factor (unstable one) was reported in the research. The study indicates social welfare measures, R&D measures, centralized power and decentralized governance measures and universal healthcare measures as independent factors. The DEMATEL analysis reveals that the net causes are social welfare measures, centralized power and decentralized government, universal health coverage measure and R&D measures, while the net effects are economic measures, green recovery measures, risk measures and international support measures.

The study includes a list of numerous government measures deployed throughout the world to mitigate the risk of COVID-19, as well as the structural links amongst the identified government measures. The Matrice d'Impacts croises-multiplication applique and classment analysis can help the policymakers in understanding measures used in combatting COVID-19 based on their driving and dependence power. These insights may assist them in employing these measures for mitigating the risks associated with COVID-19 or any other similar pandemic situation in the future.

This paper aims to create and evaluate a model for cryptocurrency adoption by investigating how age, education, and gender impact Behavioural Intention. A hybrid approach that combined partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) was used for the purpose.

This study uses a multi-analytical hybrid approach, combining PLS-SEM and ANN to illustrate the impact of various identified variables on behavioral intention toward using cryptocurrency. Multi-group analysis (MGA) is applied to determine whether different data groups of age, gender and education have significant differences in the parameter estimates that are specific to each group.

The findings indicate that Social Influence (SI) has the greatest impact on Behavioral Intention (BI), which suggests that the viewpoints and recommendations of influential and well-known individuals can serve as a motivating factor to invest in cryptocurrencies. Furthermore, education was found to be a moderating factor in the relationship found between behavioral intention and design.

Prior studies on technology adoption have utilized superficial SEM and ANN methods, whereas a more effective outcome has been suggested by implementing a dual-stage PLS-SEM and ANN approach utilizing a deep neural network architecture. This methodology can enhance the accuracy of nonlinear connections in the model and augment the deep learning capacity.

The research is based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) and expands upon this model by integrating elements of design and trust. This is an important addition, as design can influence individuals' willingness to try new technologies, while trust is a critical factor in determining whether individuals will adopt and use new technology.

Cryptocurrencies are a relatively new phenomenon in India, and their use and adoption have grown significantly in recent years. However, this development has not been without controversy, as the implications of cryptocurrencies for society, the economy and governance remain uncertain. The results reveal that social influence is an important predictor for the adoption of cryptocurrency in India, and this can help financial institutions and regulators in making policy decisions accordingly.

Given the emerging nature of cryptocurrency adoption in India, there is certainly a need for further empirical research in this area. The current study aims to address this research gap and achieve the following objectives: (a) to determine if a dual-stage PLS-SEM and ANN analysis utilizing deep learning techniques can yield more comprehensive research findings than a PLS-SEM approach and (b) to identify variables that can forecast the intention to adopt cryptocurrency.

After reading this case study, the students will be able to identify the various choices available in social e-commerce using network marketing, interpret data-driven decisions in social e-commerce and evaluate their role in scaling business, analyse cost and revenue management in value segments, evaluate technology adoption among the masses using appropriate communication structures and develop customer relationships and manage their sentiments in the era of social media.

DealShare became a unicorn in 2022 and targeted the rural and low-income groups. Based on a networking model for customer acquisition and a hyperlocal supply chain model, DealShare is increasing its customer base at a rapid pace. However, profitability was still a challenge, and converting high volume into high value continued to be a daunting task. This case study delves deep into the challenges co-founder Sourjyendu Medda and the DealShare team faced. It seeks to address key issues: how should DealShare leverage customer network for faster customer acquisition and how should they increase ticket size and profitability? As a data-driven business, what advantages does DealShare have in influencing customers’ buying behaviour using data? Dependence on social media could have a cascading effect on “word of mouth”. How can they manage customer complaints and increase engagement?

This case study has the potential to be used in different settings. In strategic cost management, this case study can demonstrate strategies for cost management in the value-conscious segment. This case study can be used in marketing management courses while teaching “positioning” in business-to-consumer markets and CRM. For second-year management students, this can be used in entrepreneurship and strategic management courses to demonstrate the network effect in social e-commerce start-up businesses. This case study is also relevant for various course modules in graduate management programmes to demonstrate the power of data-driven decision-making in business.

Teaching notes are available for educators only.

CSS 8: Marketing

This paper hypothesized that perceived relative advantage and perceived compatibility would have a positive effect on merchants' intention to accept payments via P2P mobile payment services, while perceived financial risks and perceived costs would have a negative effect. The study also explored the differences in gender, age and experience.

The proposed model is based on the valence framework, where positive utility is represented by relative advantage and perceived compatibility, while negative utility is represented by perceived risks and perceived costs. The data for this study were collected from small business owners (merchants) at the largest public market in the Center Department of Mirebalais, Haiti, using a purposive sampling method.

The results of a structural equation modeling on a sample of 339 merchants only confirmed the effect of both perceived comparative advantage and perceived compatibility. Furthermore, the multigroup analysis revealed that the perceived comparative advantage is stronger for female merchants, older age groups and merchants who frequently used P2P m-payment for the transfer of remittances. Perceived compatibility is stronger for male merchants, younger age groups and merchants who occasionally used P2P m-payment for the transfer of remittances.

This study was conducted in the economic context of Haiti, where P2P m-payments are commonly used for transferring remittances. Since there are limited studies that examine P2P m-payment acceptance from the perspective of merchants, this study offers valuable insights.