The present study attempted to assess the impact of fundamental ratios on the share prices of selected telecommunication companies in India. India has dramatically expanded over the past ten years to become the second-biggest telecoms market worldwide, with 1.17 billion users. The Indian telecom industry has proliferated thanks in part to the government of India’s liberal and reformist policies and strong customer demand. It has become a lucrative investment sector for investors due to its recent and prospective growth. Data on 13 telecom firms indexed in the S&P BSE telecommunication index from 2013 to 2022 were taken from companies’ annual reports, the BSE website (Bombay Stock Exchange), and other secondary sources. Six firm-specific fundamental factors viz. Debt to Equity ratio (D/E), Current ratio (CR), Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to earnings ratio (P/E), Return on equity (ROE), and three country-specific fundamental factors viz. Gross Domestic Product, Inflation rate, and S&P BSE Sensex return were considered. Fixed effect panel regression through Generalized Least Square (GLS) model was performed to find inferences. Debt Equity ratio and Inflation rate were found to impact share price negatively. Conversely, the Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to Earnings ratio (P/E), and Return on Equity (ROE) positively impacted selected companies’ share prices. The study results will benefit individual & institutional investors in formulating their investment and portfolio diversification strategies for gaining a high effective rate of return on their investments.

The main objective of this article is to analyze the relationship between increases in freight costs and inflation in the markets due to the increases reflected in the prices of the products in some economies in destination ports such as the United States, Europe, Japan, South Africa, the United Arab Emirates, New Zealand and South Korea. We use fractionally integrated methods and Granger causality test to calculate the correlation between these indicators. The results indicate that, after a significant drop in inflation in 2020, probably due to the confinement caused by the pandemic, the increases observed in inflation and freight costs are expected to be transitory given their stationary behavior. We also find a close correlation between both indicators in Europe, the United States and South Africa.

Purpose: The aim of the study is to apply policy analysis matrix (PAM) to identify international competitiveness of marketing channels and policy impacts of government on each marketing channels. Methodology: Policy analysis matrix is employed to evaluate influences of macroeconomic policy on the Tuong-mango value chain. The study investigated 213 sampling observation of eight main actors in chain. Findings: The findings indicate that although domestic channel 4 exhibits competitiveness (Private cost ratio (PRC) < 1), channels 1, 2, and 3 possess both comparative and competitive advantages (PRC < 1, Domestic Resource Cost (DRC) < 1, and social benefit-cost (SBC) > 1). The government’s strategy on production protection, referred to as Nominal protection coefficient on tradable output (NPCO) 0.16, together with the plan for enhancing added value, denoted as Effective protection coefficient (EPC) 0.14 and Subsidy ratio to producers (SRP) −0.18, place a significant emphasis on the first export channel. The government’s subsidy plan grants preferential treatment to Channel 4 in terms of the pricing of commercially available products, with a Nominal protection coefficient on tradable input (NPCI) value of 0.75. A value-added strategy is implemented for export channels 2 and 3, which have EPCs of 0.76 and 0.85, respectively. Policy implications: If the tradable cost is modified by 20%, there will be a change in the ratio of DRC, SBC, EPC, and SRP. While the EPC does not see a 20% reduction in domestic prices, the DRC and SBC do benefit from this cost reduction. A reduction of 20% in the local cost, coupled with a corresponding rise of 20% in the Free on Board (FOB) price, would result in a significant elevation of the SRP for export channels 1, 2, and 3. Conclusion: This is as evidence for the combination of quantitative is a dynamic tool in the policymaking process to ensure targets, constrictions, and consistent policies for agricultural fields. This permits policies to be changed in steps with an alteration in the economy and priorities set up for the tropical fruits and vegetables field.

This study investigates the impact of supply chain agility on customer value and customer trust while investigating the role of price sensitivity as a mediating variable in the healthcare industry. A quantitative methodological approach was used. This was cross-sectional descriptive research based on a survey method, and data were collected using a structured questionnaire. The sample consisted of 384 respondents who had already used healthcare facilities. The sampling technique was convenience sampling and collected data were analyzed using structural equation modeling. The study indicated that supply chain agility positively impacts customer value and customer trust, while there is no moderation role of price sensitivity in the healthcare industry. Previous scholars revealed that there is a strongly available association between supply chain agility and customer value. But no attempt was undertaken to investigate the impact of supply chain agility on customer trust while moderating the role of price sensitivity.

This study investigates the role of property quality in shaping booking intentions within the dynamic landscape of the hospitality sector. A comprehensive approach, integrating qualitative and quantitative methodologies, is employed, utilising Airdna’s dataset spanning from July 2016 to June 2020. Multiple regression models, including interaction terms, are applied to scrutinise the moderating role of property quality. The study unveils unexpected findings, particularly a counterintuitive negative correlation between property quality and booking intentions in Model 7, challenging conventional assumptions. Theoretical implications call for a deeper exploration of contextual nuances and psychological intricacies influencing guest preferences, urging a re-evaluation of established models within hospitality management. On a practical note, the study emphasises the significance of continuous quality improvement and dynamic strategies aligned with evolving consumer expectations. The unexpected correlation prompts a shift towards more context-specific approaches in understanding and managing guest behavior, offering valuable insights for both academia and the ever-evolving landscape of the hospitality industry.