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The purpose of this paper is to optimize the processing conditions of ready-to-eat (RTE) milk “coagulum” rings.

Milk “coagulum” rings were prepared from milk coagulum. Milk at four different level of milk fat (0.1, 1.5, 3 and 4.5 percent) were used to obtain milk coagulum of four different fat level for preparing milk “coagulum” rings. Unripe banana powder (UPB) and banana peel powder (BPP) were incorporated at three different levels separately. The incorporation levels were also optimized to be 11 percent for UPB and 6 percent for BPP on the basis of sensory evaluation.

The yield, ash, moisture and total dietary fiber content of products with optimized level of UPB and BPP were significantly higher as compared to control while the protein and fat contents were lower. Incorporation of extenders resulted in a significant reduction in the color value of the treated products. The water activity was highest for T₂ and lowest for control at the end of 42 days. TBARS as lipid oxidation parameter was highest for control and the microbial count was comparable in T₁ and T₂ where as it was higher in control. The sensory scores of the control was higher than the two treated products during the entire storage period.

The shelf stable RTE milk coagulum-based snack using 1.5 percent fat can provide a nutritious, palatable and healthy product to the consumers.

The intent to start an entrepreneurial venture is predisposed by certain personality traits. The study aims to analyze the impact of various identified personality traits and entrepreneurial education on entrepreneurial intentions of management students.

The data for the study were gathered from 440 students of top 5 management institutes in India. The study used a cross-sectional design and structured questionnaire based on seven-point Likert scale and was administered employing a purposive sampling method. Structural equation modeling (SEM) was utilized to validate posited hypotheses in the study.

The study discerns that apart from agreeableness dimension of personality traits, all remaining identified dimensions along with entrepreneurial education had a significant influence on entrepreneurial intentions of management students with need for achievement emerging as the most important enabler. Conscientiousness was the major dimension among big five personality traits bearing a positive influence, while neuroticism registered a negative impact on entrepreneurial intentions. In addition, results bespeak that entrepreneurial education partially mediates the effect of need for achievement, locus of control and innovativeness on entrepreneurial intentions.

The compendious model proffered in the study might be helpful for students, educators, consultants, financial institutions and policymakers in appreciating the gravity of underlying personality traits.

There is a dearth of research on big five personality traits and entrepreneurial education as enablers of entrepreneurial intentions. The study attempts to integrate big five personality traits model with dimensions of need for achievement, locus of control, innovativeness and entrepreneurial education for management students in India.

Natural calamities like earthquakes, floods and epidemics/pandemics like COVID-19 significantly disrupt almost all the supply networks, ranging from medicines to numerous daily/emergency use items. Supply Chain Resilience is one such option to overcome the impact of the disruption, which is achieved by developing supply chain factors with Artificial Intelligence (AI) and Big Data Analytics (BDA).

This research examines how organizations using AI and BDA can bring resilience to supply chains. To achieve the objective, the authors developed the methodology to gather useful information from the literature studied and developed the Total Interpretive Structural Modeling (TISM) by consulting 44 supply chain professionals. The authors developed a quantitative questionnaire to collect 229 responses and further test the model. With the analysis, a conceptual and comprehensive framework is developed.

A major finding, this research advocates that supply chain resilience is contingent upon utilizing supply chain analytics. An empirical study provides further evidence that the utilization of supply chain analytics has a positive and favorable effect on the flexibility of demand forecasting to inventory management, resulting in increased efficiency.

Few studies demonstrate the impact of advanced technology in building resilient supply chains by enhancing their factors. To the best of the authors' knowledge, no earlier researcher has attempted to infuse AI and BDA into supply chain factors to make them resilient.

Despite efforts to reduce environmental pollution and wasteful fossil fuel use, electric vehicles (EVs) are still rare on the road. Why is it so challenging to get widespread EV adoption? One significant factor on which it heavily depends is one's awareness and understanding of EVs. However, due to an absolute lack of knowledge on the part of the populace, this factor becomes a huge impediment to the uptake of EVs. A systematic review of the electronic database Scopus for the years 2003–2022 was carried out on ‘EV awareness and adoption of EV’ while considering the ‘Preferred Reporting Items for Systematic Reviews and Meta-analysis’ (PRISMA) standards. A three-step identification process resulted in the ultimate detection of 41 papers, which were then thoroughly examined. A conceptual framework that encompasses the three key awareness aspects that influence EV adoption is developed. To encourage greater uniformity among EV researchers, this study's conclusions serve as a foundation for operationalising upcoming research efforts within a predetermined framework. The authors must therefore be optimistic that lingering technological, legislative, cultural, behavioural and business-model barriers may be overcome over time through widespread dissemination of knowledge and awareness related to EVs, making it possible for everyone to switch to greener, more economical and more efficient transportation solutions.

Social entrepreneurship is an area that has been extensively researched from a variety of angles and across a broad range of academic disciplines. Parallel to this, practitioners have applied social entrepreneurship ideas to a variety of industries and at varying degrees of complexity. The purpose of this study is to understand how the social capital of an entrepreneur drives the growth of social enterprises by contributing to the social entrepreneur skills. A systematic assessment of available literature was carried out based on searches of major academic databases (Web of Science, EBSCO and CAPES Portal de Periódicos), with an initial list of 3,106 publications being narrowed down to 472 articles that were subjected to content analysis after being narrowed down. Further, a theoretical proposal and research propositions were developed, highlighting the relationship between social capital and the activities of social entrepreneurs, as well as their relationships with the collective actors and institutions that make up social entrepreneurship in its totality. The conclusion of the chapter is that the interface between social entrepreneurship and social capital is a latent field for research. Further contributions of the chapter are a theoretical model to help researchers consolidate their efforts by identifying three key themes identified by intensive literature: creation of social capital by the social entrepreneur, relationships between institutions and the formation of groups and social capital as a formation of groups. In these words, a future agenda for discussing these topics is outlined for discussion.

The study aims to highlight the barriers faced by the entrepreneurs toward achieving sustainability in business and innovation cultivation by offering solutions for academicians, practitioners and policymakers. The study uses the resource-based view (RBV) theory to discuss how an organization’s resources and capabilities influence the competitive ambience and barriers faced by entrepreneurs.

The present research uses grey-causal modelling (GSC) to analyse the barriers against successful entrepreneurship.

The research focuses on the usefulness of dynamic capabilities, managing and cooperating resources in the entrepreneurship setting. The paper highlights the importance of resource gathering and nurturing as a method to combat scarcity. This research further identifies that financial limitations, regulatory obstacles, challenges to sourcing qualified labour, poor infrastructure and technology, limited mentorship opportunities, lack of scalability, low initial cost barriers in product development and risk-averse attitudes are the major factors hindering entrepreneurs from obtaining sustainable business and innovation.

The contribution of this research to the literature is that it assesses RBV theory within the realm of entrepreneurship, providing a different perspective on resources and capabilities as well as the challenges faced by entrepreneurs. The systematic approach to the analysis and prioritization of various barriers is innovative, and it adds knowledge in this area.

Recent technological advancements, often linked to Industry 4.0, require organizations to be more agile and innovative. Blockchain technology (BT) holds immense potential in driving organizations to achieve efficiency and transparency in supply chains. However, there exist some insurmountable challenges associated with the adoption of BT in organizational supply chains (SC). This paper attempts to categorically identify and systematize the most influential challenges in the implementation of BT in SC.

This study resorts to an extensive literature review and consultations with experts in the field of supply chain management (SCM), information technology and academia to identify, categorize and prioritize the major challenges using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Combined Compromise Solution method (CoCoSo).

The top three classes of challenges revealed in this study are privacy challenges (PC), infrastructure challenges (IC) and transparency challenges (TC). Maintaining a balance between data openness and secrecy and rectification of incorrect/erroneous input are the top two challenges in the PC category, integration of BT with sustainable practices and ensuring legitimacy are the top two challenges in the IC category, and proper and correct information sharing in organizations was the top most challenge in the TC category.

Future scholars and industry professionals will be guided by the importance of the challenges identified in this study to develop an economical and logical approach for integrating BT to increase the efficiency and outcome of supply chains across several industrial sectors.

This paper aims to identify various macroeconomic variables that affect the stock market performance of developed and emerging economies. It also investigates the effect of these factors on the stock markets of both economies. The impact of these variables on broad market indices and sectoral indices is investigated and compared too.

The publications for the study were retrieved from databases such as Emerald Insight, EBSCO, ScienceDirect and JSTOR using the keywords “Macroeconomic variables” and “Stock market” or “Stock market performance.” The result demonstrated a growing corpus of scholarly work in the domain of stock market. The study was carried out separately for each macroeconomic indicator. Given a large number of articles under consideration, the authors began by reading the titles and abstracts of all publications to identify those that were relevant. The papers are evaluated in Excel and the articles for review range from 1972 to 2021.

The authors found that gross domestic product (GDP), FDI (Foreign Direct Investment) and FII (Foreign Institutional Investment) have a positive effect on both emerging and developed economies’ stock market while gold price has a negative effect. Interest rates had a negative impact on both economies except for a few developing countries. The relationship with oil prices was positive for oil exporting countries while negative for oil importing countries. Inflation, money supply and GDP are the macroeconomic variables that have the same effect on sectoral indices as they do on broad market indices. The impact was sector-specific for the remaining variables.

This paper gives an overview of relation and effect covering variety of macroeconomic variables and stock market indices. Still, there is a scope for further research to analyze the effect on thematic, strategy and sectoral indices. A longer time horizon with new variables, such as bank deposit growth rate, nonperforming assets of banks, consumer confidence index and investor sentiment, can be studied using high-frequency data. This research may help stakeholders adopt and manage their policies during a crisis or economic slump.

This study will assist investors, researchers and educators in the fields of economics and finance in understanding how macroeconomic factors affect the stock market. Furthermore, this study can guide in portfolio diversification strategy across multiple sectors by examining the impact of macroeconomic factors specific to sectoral indices. This paper provides insight into society and researchers since it integrates a number of macroeconomic variables and their interaction with the stock market. It may also help pension funds and mutual fund firms to hedge their funds and allocate equity portfolios.

With respect to India, this study looked at new macroeconomic variables and sectors. It contrasted the impact of these variables in developed and developing economies. The effect of broad and sectoral stock indexes was also investigated and compared. The authors examined how these variables responded during crisis and economic downturns by using articles from a longer time frame. This research also looked into how changing the frequency of data for the variables altered stock performance. This paper emphasized the need for more research into thematic, strategy and broad market indices, such as small-cap and mid-cap indices.

The adoption of metaverse in manufacturing holds significant benefits, but there are several barriers to its seamless integration. This paper aims to identify such barriers and prioritize them in a manner that allows industrial leaders to strategize for smooth adoption.

In this study, we applied two-stage methods, first the identification and validation of barriers through an empirical study applied to Exploratory Factor Analysis (EFA). A purposive sampling technique and snowball sampling facilitated data collection from these expert sources. Through snowball sampling, additional contacts working in the metaverse field were reached, resulting in 235 possible respondents; the survey yielded 104 completed responses. Thereafter, the best-worst method (BWM) was used to measure and rank the barriers.

The study results show that the two most critical barriers are “Lack of data security and privacy” and “Lack of integration compatibility with existing systems.” Such findings inform industry leaders of specific recommendations for structural changes, training programs, necessary technological investments and collaborative efforts to overcome these barriers.

This work adds significantly to academic discussion by prioritizing barriers towards integrating metaverse technology in manufacturing. In addition, this strategic methodology aids in critical appraisal and ranking of barriers for successful adoption. This study also identifies key barriers but acknowledges that other unexamined factors might be lurking in the background, such as virtual economy, financial risks and cross-border legal issues.

The study’s conclusions cannot be generalized to the other sectors, thus indicating the necessity of carrying out a comparative multi-sector study in the future.

To the best of the authors’ knowledge, the study on systematic prioritization of barriers to adopting metaverse technology in manufacturing is the original contribution of the authors.