Contemporary Business Practices and Sustainable Strategic Growth

In the context of Indian socio-economic conditions, crowdfunding is emerging as a powerful tool for fostering an inclusive future platform through digital innovation and technological expertise. As an efficient and economical method of raising funds, crowdfunding has the potential to bridge the supply-demand gap, raise awareness for causes at the grassroots level, and initiate matching funds systems with organizations. Simultaneously, corporate social responsibility (CSR) supports sustainable production and consumption across various social sectors, such as education, clean water, health, poverty alleviation, renewable energy, and gender equality, addressing economic, social, and environmental dimensions holistically. With the enactment of the Companies Act of 2013, the Government of India has made CSR mandatory, imposing a statutory obligation on companies to promote CSR projects aimed at advancing social welfare. Since 2015, Indian companies have collectively raised over ₹9,300 crores for social projects, driven by the understanding that consumers increasingly trust and prefer organizations that are socially conscious and give back to society. This paper attempts to empirically analyze data on socially inclined crowdfunding initiatives and their impact on the growth of CSR activities, particularly in the areas of education, health, environmental sustainability, and women’s empowerment, from 2015 to 2023. We assess the multifaceted impact of crowdfunding on CSR initiatives that promote social well-being and welfare in the Indian context over the last decade. Specifically, the paper focuses on the journey of platforms that have utilized crowdfunding beyond the materialistic goal of profit, embracing a broader vision of sustainable development for society. It also explores the success rates and challenges faced by socially inclined funding projects, aiming to inform future policy-making processes.

The difficulty in understanding the impact of social antecedents on employee intention-to-stay is a challenge that many HR professionals face. This challenge becomes particularly pronounced in the context of Information Technology (IT) companies in India, where the focus has traditionally been on organizational, psychological, and contextual factors affecting employee retention. Social antecedents, which encompass variables like relationships with co-workers, supervisors, organizational culture, and the overall work environment, have often been overlooked in research within this industry. Social antecedents play an important role in shaping employee behavior and intentions in the workplace. Positive relationships with co-workers and supervisors, a supportive organizational culture, and a conducive work environment can significantly impact an employee's decision to stay with their organization. Conversely, negative social interactions or a toxic work environment can lead to dissatisfaction and ultimately drive employees to seek opportunities elsewhere. Most of the prevailing research have mainly revolved around organizational, psychological, and contextual factors as drivers affecting employee intention to stay. Considering the logic that there is an existing gap in whether social factors have any role in influencing employee intention to stay, this study aimed to explore the role of specific social factors—such as “support from the supervisors”, “co-worker support”, “external social support”, and “social networks”—on employees' intentions to remain with Information Technology companies located in and around Delhi.

Through a questionnaire survey distributed among 300 employees representing various IT organizations in and around Delhi, the research uncovered that support received from the supervisors played a mediating role in influencing the link between “coworker support”, “social networks”, and employees’ intention-to-stay. 

The rapid expansion of technology and healthcare sectors has triggered a notable upsurge in waste production, notably in medical and electronic forms, posing significant environmental and public health dilemmas globally. Consequently, the concept of sustainable management of natural resources has emerged as a comprehensive approach to mitigate the adverse impacts of waste generation and disposal. This research endeavours to pinpoint challenges, innovative solutions, and best practices in sustainable natural resource management, particularly concerning medical and e-waste. Employing a thorough examination of literature, case studies, and empirical analysis, this study delves into the intricacies of waste management, placing emphasis on principles such as waste minimization, resource recovery, and circular economy approaches. By elucidating the interplay of environmental, social, and economic factors in shaping waste management strategies, the research probes the implications for broader environmental sustainability objectives. Offering practical insights, this study seeks to empower policymakers, industry stakeholders, and researchers in devising sustainable strategies for the management of medical and ewaste. Drawing from diverse geographic regions and sectors, current scenarios are analysed to provide actionable recommendations for establishing resilient and resource-efficient waste management systems. Ultimately, this research adds to the ongoing conversation on sustainable waste management practices, paving the way for a more resilient and resource-efficient future.

Augmented reality, a technology that merges computer-generated content with real-world environments, has gained popularity due to the surge in e-commerce, particularly during the COVID-19 pandemic. E-commerce offers convenience, global reach, and cost efficiency for businesses and consumers, but lacks physical touchpoints. Augmented Reality (AR) has transformed consumer happiness by allowing them to virtually experience a product, providing a better understanding of its potential for purchase. This systematic review investigated the role of Augmented Reality (AR) in enhancing the online shopping experience.

Research Methodology
Secondary data resources such as journals, books, research papers, appropriate websites, and newspapers were contemplated for this study.

Research Gap
The review reveals that studies have overlooked the technical limitations of Augmented Reality (AR), as it heavily relies on device hardware and connectivity, affecting customer experiences.

Results
Augmented Reality enhanced online shopping experiences by allowing customers to try products, improving purchase decisions, and increasing customer satisfaction which fostered trust between organizations and customers.

Conclusion
The COVID-19 pandemic has accelerated e-commerce growth, necessitating the use of Augmented Reality to improve customer shopping experiences and stay competitive in the digital world.

In the automotive sector, technological innovation is the ongoing creation and application of novel and cutting-edge technologies to improve a range of vehicle attributes. This covers enhancements to automation, connectivity, energy efficiency, safety features, and general performance. Artificial intelligence, sensors, electric propulsion, and advanced materials are some examples of innovations that can be used to create safer, more environmentally friendly, and feature-rich vehicles that satisfy changing consumer and regulatory requirements.

In this study, we gathered secondary data sources from all over the world, including journal articles, case studies, research papers, and newspaper pieces about some market automobile leaders. This study examines consumer attitudes and views of self-driving cars, electric vehicles, and brand preference, focusing on how public opinion is shaped by safety concerns, media attention, and trust. Consumer tastes and environmental awareness are the main topics of this study. Examining the impact of sustainability and environmental friendliness on consumer happiness and brand loyalty can affect consumer choices, including the need for hybrid and alternative fuel vehicles as well as advanced connectivity capabilities and entertainment Systems, utilizing consumer preferences, manufacturers create innovative technologies that satisfy market demands and boost industry competitiveness, customer satisfaction, and the uptake of cuttingedge features. The successful and sustainable growth of the automotive industry is ensured by the interaction between technological innovation and consumer preferences, resulting in the creation of vehicles that meet consumer needs.

This paper examines the impact of social media on hotel brand image, which aids in retaining loyal customers. It also explores how social media influences customer preferences in selecting a specific hotel, leading to overall satisfaction. Data was collected using conventional sampling, and multiple regression analysis was employed to assess the influence of various social media attributes on brand image and brand loyalty in the hotel industry. Secondary data was gathered from previous research, while primary data was collected through a structured questionnaire. The analysis reveals that attributes such as e-WOM (Electronic Word of Mouth), e-Ads (Electronic Advertisements), and e-Community (Electronic Community) positively impact brand image, thereby strengthening customer loyalty. This research provides hotel management with insights on leveraging social media to enhance brand value and profitability, while also highlighting potential risks associated with social media used to foster a stronger brand image and enhance guest loyalty.

Job satisfaction is an exclusive way to measure an employee's sense of belonging and dedication to the company. Contrarily, productivity is the ratio of inputs that an individual or organisation invests in and outputs that the organisation can acquire through funds, employee potential and expertise, efforts, profit-making ability, and other resources in exchange for achieving its objectives. The use of technology and Digitisation in the workplace has a significant impact on employee satisfaction. Employees who are satisfied with their jobs will be more likely to stay with a company and be happier in their work life. With the ever-changing nature of the competitive market, every organisation must have a positive outlook towards the overall productivity rate for their long-term sustainability. In this study, some higher educational institutes in West Bengal were considered to analyse the overall scenario of their employee satisfaction and productivity rate. For this purpose, some existing data have been taken into account throughout the study. The main objective is to explore the different facets of employee satisfaction and the various factors affecting the entire scenario in this digital era.

Amidst the myriad changes unfolding in the realm of digital markets and consumer behavior, individuals' shopping habits have undergone a profound transformation. Leveraging the purchase history of customers, personalized product recommendations are now ubiquitous across the web, courtesy of Artificial Intelligence (AI). However, the extent of AI’s impact on fostering customer repurchase intention remains a pertinent question. This study aims to elucidate the influence of AI-driven purchasing applications on consumer repurchase intention, employing a comprehensive methodology that integrates both qualitative and quantitative approaches. Data were gathered using Likert's 5-point scale and subsequently analyzed through factor analysis and multiple regression analysis. The results of this research make a significant contribution to the e-retail sector, offering valuable insights into user behavior and addressing gaps in academic research.

Forecasting stock market returns poses a formidable challenge due to the inherent volatility and non-linear dynamics of financial markets. The main objectives of this research are to predict the stock closing price of FAANG companies where FAANG is the acronym for five of the best-performing techs-centric stocks of the past decade: Facebook (now Meta Platforms), Amazon, Apple, Netflix, and Google (now Alphabet). Harnessing strides in artificial intelligence and heightened computational capacities, this research deploys intricate predictive methodologies to augment the precision of stock price prediction. In this work, we have utilized 8 different Machine Learning models such as Linear Regression, KNN Regression, Decision Tree Regression, Random Forest Regression, AdaBoost Regression, Gradient Boosting Regression, XGBoost Regression and CatBoost Regression for predicting the closing price of FAANG companies. The models are evaluated on the basis of R2 score, MAE, MSE, and RMSE. Low values of MAE, MSE, and RMSE and a high score R2 score indicate the high efficiency of the model. Gradient Boosting, XGBoost, and Catboost excel in MSE and MAE metrics. Linear Regression excels for Google and Meta but falters elsewhere. Decision Tree and Random Forest exhibit diverse performance, while K Nearest Neighbors Regressor performs inadequately, suggesting unsuitability for this dataset. It has been observed that greater data variability, as indicated by a wider range, is associated with lower prediction accuracy in the model. This study aims to help financial analysts, investors, and managers get a wider perspective of the performance of the various machine learning models based on the various error metrics and how they are effective for next-day prediction.

Over the past 20 years, scholars and policymakers have focused more on financial inclusion as a possible source of economic advantages. From a research perspective, the investigation of financial inclusion can be seen as a natural progression from the early 1990s literature, which revealed favourable macro and microeconomic effects of more effective financial service delivery overall. For instance, it has been demonstrated that the wide process of financial development encourages economic growth at the business, industry, and national levels in addition to improving resource allocation and productivity growth, which in turn has some bearing on capital accumulation.

Micro, Small, and Medium Enterprises (MSMEs) play a significant role in driving economic development through their significant contributions to employment generation, Gross Domestic Product (GDP) growth, and overall industrial advancement. These enterprises, often characterized by their agility, innovation, and local focus, have a profound impact on various aspects of an economy.

The government of India right from the beginning through different stakeholders started financial inclusion programmes. Although there was an initiative on behalf of the Government of India with different stakeholders from time to time for financial inclusion, the process got a major Philip with the onset of digitisation. With the system being online, any sort of registration has become easier compared to earlier times and MSMEs have become more formalised with Udyam Registration thus leading toward financial inclusion. The result of trend analysis with 5 factors e.g, popular government schemes like PMEGP, MSME Samadhan Portal-“MSME-SAMBANDH Portal”-GeM Portal on financial inclusion shows mixed results. 

In today's society, the role of AI or Artificial Intelligence is undeniable. In this data-driving world, the financial sector is also not an exception to technological advancements. This article will focus on the role of AI in reshaping the investment behaviour of individuals in the era of the digital economy. The researchers have introduced the concept of AI and how it can impact the investment landscape. From this study, one would understand that AI can make strong strategies for individuals to invest correctly and in the way it can be managed. The researchers have conducted a systematic literature review to complete this study. A total of 26 articles have been selected at the final stage for being reviewed among 150 articles. The researchers used PRISMA software to structure the database for this study. Moreover, the research protocol has been made which shows the research objectives along with the conceptual boundaries as well as some inclusion criteria. Considering those inclusion and exclusion criteria, researchers have developed three themes to understand how AI can reshape an individual's investment behaviour. The results of this study show that AI can influence the investment landscape and recognise the pattern of human investment behaviour by using AI-driven algorithms. This can further strengthen the position of the financial sector across the digital economy. This study is also supported by the research limitations and future scope that can reduce the research scope positively. 

Pattachitra is an ancient art and craft of India as well as West Bengal. The artisans who engage in this craft work are known as patuas. Most of the patuas originate from the Midnapore and Bankura districts in West Bengal. Patuas face significant problems in selling their beautiful craftwork. They have no fixed places or shops to demonstrate and sell their pattachitra. The curse of globalization has also hit them hard, making it difficult to continue their scroll painting. In this study, the researcher focuses on some sustainable business development strategies like Artisans to Businessman (A2B), Artisans to Tourists (A2T), Artisans to Intermediaries (A2I), Artisans to Government (A2G), and Government to Tourists (G2T). These strategies help patuas in developing and continuing their ancestral artwork. In this study, the researcher focuses on the strategies that should be adopted by the patuas for the development of their ancestral artwork and craft business, i.e., pattachitra. This paper also focuses on the SWOT analysis of those strategies.

Providing leniency is one of the discretions of competition regulators across the world. The commission, after being satisfied with the disclosure furnished by cartel conspirators, can provide a lesser penalty. Once the American Supreme Court commented, “Cartel is the supreme evil of antitrust”. Amid Covid-19 we noticed that enterprises dealing with essential commodities like pharmaceuticals, groceries, milk, etc. were allowed to share their information freely. Sharing information between competitive enterprises is anti-competitive under the purview of the Competition Act 2002.The essential commodities market had been exempted from punishment by nations across the world for the sake of public interest. Thus the public interest turned out to be the valid defence behind the operation ofthe cartel. However, the Commission ordered leniency (lesser penalty) to cartel conspirators belonging to the railway's procurement and the domestic industrial automotive bearing market. Surprisingly, the duration of operation of the cartels in the railway's procurement market was from 2009 to 2017 and in the domestic industrial automotive bearing manufacturer market was from 2009 to 2014. Although, both of them were allowed leniency due to Covid-19. It is difficult to consider any of these two as the essential commodities market. This paper intends to emphasize relevant broader perspectives and their applicability under existing law. 

This study investigates the intricate dynamics of customer behaviour during interactions with service robots, focusing on the role of meta-perception. It aims to identify major themes, influential figures, and emerging trends in the field while shedding light on the implications of discomfort in service interactions for customer experiences and its relation to meta-perception processes. This study uses bibliometric analysis and visualization methods to examine the academic discourse surrounding service robots and consumer Behaviour. It analyzes various scholarly literature to pinpoint key themes, prominent contributors, and evolving trends. The research reveals significant insights into the relationship between service robots and customer Behaviour. It highlights the concept of discomfort in service interactions, which has been relatively overlooked, and its impact on customer experiences through metaperception processes. Additionally, the study elucidates the influential role of various factors, such as eminent journals, authors, nations, and platforms, in shaping academic discourse in this field. This study contributes to understanding service robots and consumer Behaviour by uncovering novel insights and emphasizing the importance of comprehending complex interactions in service contexts. Bridging the gap between human cognition, emotional reactions, and technological advancements offers a nuanced perspective on the evolving landscape of service robots and their implications for customer experiences.

Continuously high stressed asset levels have a detrimental effect on the banking industry and, in turn, on economic expansion. Risk associated with the banking sector is therefore thought to have a significant influence on macroeconomic stability and sovereign credit risk. While there may be a variety of factors influencing the amount of stressed assets, this study explicitly examines and concludes that bank ownership in India is a significant determinant, and the effectiveness of the regulatory framework is crucial for prompt stress recognition. The recovery of non-performing assets (NPAs) requires proper credit assessment and recovery management mechanisms. Banks tend to extend credit during periods of excess liquidity and economic expansion, leading to concerns about asset quality and the potential risk of adding NPAs to the portfolio. The Indian banking sector's performance on NPA recovery routes is not up to par, primarily due to improper due diligence, inadequate legislation, and macroeconomic variables. The present paper is an analytical one, it discusses the probable factors that significantly impact the Return on Assets and Return on Equity of the Public Sector and Private Sector Banks. The independent factors identified for the study are GNPA, NNPA, Restructured Loans, Provisions, Stressed Assets, Total Advances, & Stressed Assets to Total Advances. The study is completely dependent on the secondary data, published in the RBI Portal. The statistical tool used is Regression Analysis, with the help of SPSS.

While everyone is busy trying to find a balance or equilibrium between work and personal life in the twenty-first century, many of them are unable to do so. The idea of work-life integration emerged as a result of everyone's desire to keep the two aspects of their lives apart. The idea of work-life integration, however, also represents a compromise for those of us attempting to strike a balance between our personal and professional lives. However, as highlighted in Donna Haeger and Lingham's (US) 2014 book, the notions of work-life fusion are already grabbing hold of society as a whole, particularly influencing Millenials. Managing professional and personal responsibilities at the same time is the essence of this work-life integration. In light of this context of work-life, fusion needs to wire both work and life.

Enhancing workers' abilities, knowledge, and attitudes requires training. It is usually a value-adding activity that the company does to increase the value of its resources, which are its people. Tea is one of the labor-intensive industries. The second-largest employer of skilled, semi-skilled, and unskilled workers in India is the tea sector. A large workforce is needed for everything from setting up the beds for the tea siblings to packing the finished tea. Every task involved in the manufacture and picking of tea is specialized. Hence, skilled work is required to produce tea. Furthermore, the type of personnel used has a big impact on the quality of tea. Thus, employee training is essential to creating high-quality tea. However, because of the quality issue, the Indian tea sector has lost its market share abroad. Examining the entire situation of the tea workers' training and their efficacy from this angle has been attempted. Total 33 sample tea estates were surveyed for the study purposes, and the gathered data was then examined using SPSS. The study's conclusions and suggestions have been developed using the non-parametric Wilcoxon Signed Ranks Test.

With high government measures, data-driven business, and in quest of becoming a successful startup both in terms of efficiency (value addition) and effectiveness (valuation), enterprises have been evolving globally and getting the ‘unicorn status’ in a rapid way. However, the high failure rate of the startups is putting a great question mark and thus generating an area of interest for the research world. Entrepreneurial ecosystems and related research work indicate a ‘business model’ that can be a probable solution for the problem. A business model is an architecture of value creation, its delivery, and capturing the benefits of the enterprises. Hence it is the need of the hour to scan the works on business model and startups to know what exactly drives the startup to organize their business model to be sustainable. The major components of the business model as a result of the study would be tested with the research works on unicorns, a benchmark for the startup to gain, to know the real gap among the business model literature that can be solely healed with further research works. In this study, we analyze the relevant research papers (using PRISMA), taking “business model” and “startup” as keywords from different journals. Also, a literature review is done with the keyword “Unicorn.”