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The role of logistics service provider (LSP) is essential for efficient logistics service quality (LSQ) and supply chain management, especially in multimodal transport. Multimodal transport routes that use the Trans-Siberian Railway (TSR) play an important role in the supply chains of Northeast Asia. This paper aims to identify current conditions of TSR LSQ and propose improvements to enhance the competitiveness of traditional routes. Therefore, this study sheds light on and provides recommendations for various managerial strategies to LSPs in the context of the TSR. This study utilizes Importance-Performance Analysis (IPA) to measure levels of importance and performance of the logistics service of LSPs that provide multimodal transport services via the TSR from South Korea to Europe. This study identifies capabilities on the basis of five criteria (price, timeliness, reliability, equipment systems, and customer service) from a customers’ perspective. The results of the research indicate that operational improvements should be considered to activate TSR multimodal transport for northern logistics routes from the perspective of Korean shippers. Specific findings show that balanced development strategies are needed for logistics routes that have not yet been significantly activated, while implying that logistics costs could be reduced initially to satisfy shippers. This study presents an operational strategy for LSPs using the TSR in northern logistics through IPA methods. Furthermore, this research can help policymakers propose specific policies to revitalize the northern logistics of Korean logistics companies and to provide incentive supports for shippers.

Automobile industry has been the backbone of manufacturing sector in any country. During the past decade, passenger car industry has emerged as the one of the growing sectors in the Indian economy. Technological features in the passenger cars industry has been evolving in the global market, and customers have been the most important stakeholders to judge the requirement of these features. Therefore, the purpose of this paper is to analyze the customers’ need for these emerging technologies using Kano model of customer satisfaction.

This paper has used the Kano model to assess the customer satisfaction for Indian passenger car companies. Overall, 250 customers of passenger cars from Northern India have been surveyed using well-structured questionnaire designed as per the Kano model. On the basis of responses, this study has categorized the technological attributes of passenger cars as attractive, must be, one-dimensional and indifferent.

“Auto Gear Shift” system has emerged as a must be attribute. “Premium surround system” has been categorized under one-dimensional attribute. “Communication between vehicles,” “integration with smart phone,” “connecting applications,” “dual-stage airbags,” “in-dash navigation system,” “rearview camera,” “heated and cooled seats,” “built-in fourth generation long term evolution,” “Wi-Fi system” and “automated window cleaning system” have emerged as attractive features. The customers have been indifferent about “gesture control,” “reality display on car wind screen” and “run-on-flat tyre.” In contradiction to the popular belief, this study has found that customers have shown Indifferent attitude toward “hydrogen fuel-operated cars” and “battery cars.”

This present study gives insight about the acceptability of various emerging technological features in Indian car market. This study has fulfilled the existing dearth in assessing the customers’ insight about the implementation of these emerging technologies in Indian cars. This paper will be helpful to the manufacturers to inculcate the voice of the customers in designing the new technologies for the passenger cars.

Previous studies across the globe have applied Kano model for assessing customers’ satisfaction in various industries, but according to the authors’ knowledge, hardly any study was conducted in context of technological attributes for Indian passenger car companies.

The aims of the paper are to investigate IT software and service export function for India. First, cointegration tests have been used to investigate the long-run equilibrium relationship of the given variables. Second, long-run coefficients and associated error correction mechanism are estimated.

Annual time series data on IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index have been used for the present study during the period 1980–2017. The data are collected from the National Association of Software and Service Companies (NASSCOM), Planning Commission of India, University Grants Commission (UGC) of India, real effective exchange rate (REER) database and World Bank development indicators. Auto regressive distributed lag (ARDL) model is used to analyze both short-run and long-run dynamic behaviour of economic variables with appropriate asymptotic inferences.

Results of the analysis show the stable long-run equilibrium relationship among the given variables. It is found that external demand, exchange rate, human capital and openness index have a substantial long-run impact on the IT software and service exports. We also found that the coefficient of error correction term is negative and significant at 1% of the level of significance, which confirms the existence of stable long-run relationship which means adjustment will take place when there is a short-run deviation to its long-run equilibrium after a shock.

There may be other determinants of software and service exports apart from those considered by the present study. Due to the non-availability of data, the study considers only important determinants that determine the software and service exports in India. The IT exports are an emerging and dynamic field of economic activity and the rate of change is so rapid that the relevance of individual factors may change over time. The study period is also limited to available data.

The paper has implications for achieving sustainability in IT software and service exports growth. It is recommended that policies directed at improving the performance of IT software and service exports should largely consider the long-run behaviour of these variables.

This paper focuses on originality in the analysis of the relationship among the given variables including IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index in India. All the work has been done in original by the authors, and the work used has been acknowledged properly.

The objective of the paper is to investigate the relationship between financial risk and the value of the company. In this context, the study is to revisit the trade-off theory of capital structure in the Indian context.

After applying outlier, the study considered 389 nonfinancial companies from BSE500 from 2001 to 2018 collected from the Capitaline database. The statistical package E-views 10 has been utilized for analysis. To understand the nature of the data the descriptive analysis, correlation analysis, normality, unit root, multi-collinearity and Heteroskedasticity were conducted. The Panel Estimated Generalised Least Square with cross-section weight was found suitable for analysis due to the existence of cross-correlated residuals. Further, the study has classified the levels of financial risk to determine the relationship of different levels of financial risk with corporate value.

It was found that the financial risk and corporate value had a significant negative relation during the period of study. On class interval-wise financial risk analysis, it was found that the debt-equity (DE) of around 1:1 may be considered optimal. Below that threshold limit, the DE affects value positively above which the ratio affects the value negatively.

The paper makes an attempt to determine the optimal financial risk at the corporate level in the Indian context.

The study attempts to examine the impact of mandatory corporate social responsibility (CSR) spending and inclusion of firms into the environment, social and governance (ESG) index of BSE India on the performance of firms constituting firms under the Bombay Stock Exchange (BSE) 100 Index.

The stock prices of the firms were collected from the official website of BSE India for a total of 32 firms and the System Generalized Method of Moments (GMM) model was utilized for analyzing the data for the present study.

The study found that the investors in the Indian market do consider the CSR spending and ESG listing as a factor while framing the investment strategy; however, ESG listing is least preferred. Among the other variables, AGE, DPS, EPS and BVPS have a significant positive bearing on the firm's performance, while SIZE has a significant negative impact on the firm's performance.

Further investigation is needed to understand the factors that influence investment decision-making, including why investors tend to overlook CSR and environmental protection. Future research can identify ways to increase the importance of these factors in investment decision-making. Future research can explore the long-term impact of investing in socially responsible companies, including whether such investments lead to better long-term performance.

There is a need for increased awareness of the importance of CSR among investors. Educational programs and campaigns can be used to inform investors about the potential benefits of considering social responsibility factors in investment decision-making. Companies that prioritize CSR and environmental protection should distinguish themselves from competitors in the eyes of investors. This can lead to higher investment and potentially higher returns for these companies.

Since mandatory CSR expenditure and the launch of the ESG index by the BSE have been introduced in India recently, hardly any study in India has examined the impact of the same on the firm's performance.

The COVID-19 situation affected the whole landscape of retailing in India and around the world. However, some businesses have used the pandemic-related difficulties into opportunities. E-tailing is one of the ways that helped people in India to continue shopping their essential products and choosing their luxury products without making any physical visits during the lockdown. This research understands the current situation through an observation study and suggests the e-tailing model suitable during the COVID-19 and beyond.

We used secondary data to make the observational study. We also conducted two case studies and interviews with grocery shops and an automotive company.

This research suggests a simple collaborative e-tailing model combining all supply chain players to reduce people’s movement, timely delivery and enhanced service to meet customers demand during the lockdown period.

This paper has considered two real cases for discussion and also obtained information from public domain. The proposed model has been discussed with the case companies, and it hoped to support business planning for online services.

The study aims to explore the argument of implementing the lean method to part or whole of an operation by examining the moderating impact of varying levels of the extent of implementation of four different lean methods, along with their functionalities, in predicting productivity improvement (PI).

As the focus of understanding the efficacy of lean principles is shifting from process to industry level, this study tried to generalize the approach by gathering data from 132 large Indian auto component manufacturers. This involves an assessing/monitoring approach rather than measurement.

Results highlighted the interdependence or individuality of the extent of implementation of lean methods and their functionalities. Findings revealed a significant moderating effect in improving productivity to a greater extent of 50%.

Adopting an assessment approach to a measurement study provides a noteworthy contribution to bridging theory and practical consequences. The findings can be appropriately extrapolated to medium and small enterprises forming a critical connection in the entire automobile manufacturing ecosystem.

The study showed that even if a lean method is applied to a certain extent of operations the chances of PI are significant. This is important for decision makers as they confront problems of optimum resource allocation.

PI, reduced cost and generalization of results would enable the auto component industry to become more competitive.

The examination of the moderation effect of a lean principle implementation extent, along with that of its functionalities to predict the improvement in productivity from its existing level, is a major outcome of this study.

In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.

The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.

The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.

The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.

The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.

The purpose of this paper is to examine if certain board characteristics have an impact on the financial performance of manufacturing firms in India.

The study draws on data from 275 firms listed in NSE during from 2011 to 2015, using a multiple regression model. The present study examines the effect of board characteristics such as board size, CEO duality, independence and board activity devoted to the effectiveness of firms performance regarding market and accounting based financial performance measures.

The finding supports an inverse association between the extent of board characteristics and the firms’ performance indicators. The study also finds a statistically significant negative relationship between board size and Tobins Q, ROA and ROE. The evidence also shows that the board independence and meeting frequency moderate the relationship between return on equity and return on assets by enhancing these measures among corporate governance mechanisms.

The present study does not include all possible board characteristics, i.e., large shareholders dominance on the board and promoter’s and institutional shareholding, to support firm’s performance. Further research might include the ownership structure of the board to improve firm’s performance.

The study focuses on the corporate governance issues such as size, duality, independence and activity of the boards and their influence on firm performance. The subject analyzes the possible impact of board characteristics and firm-related features that have received much attention from academic research, which has largely focused on studying the publications of corporate governance in India and Asian context.

This paper aims to analyze the impact of Covid-19 on the stock market volatility and uncertainty during the first and second waves.

This study has applied event study and autoregressive integrated moving average models using daily data of confirmed and death cases of Covid-19, US S&P 500, volatility index, economic policy uncertainty and S&P 500 of Bombay Stock Exchange to attain the purpose.

It is observed that, during the first wave, the confirmed cases and the fiscal measure have a significant impact, while the vaccination initiative and the abnormal hike of confirmed cases have a significant impact on the US stock returns during the second wave. It is further observed that the volatility of Indian and US stock markets spillovers during the sample period. Moreover, a perpetual correlation between the Covid-19 and the stock market variables has been noticed.

At present, the world is experiencing the third wave of Covid-19. This paper has considered the first and second waves.

It is expected that business leaders, stock market regulators and the policymakers will be highly benefitted from the research outcomes of this study.

This paper briefly highlights the drawbacks of existing policies and suggests appropriate guidelines to successfully implement the forthcoming initiatives to reduce the catastrophic impact of Covid-19 on the stock market volatility and uncertainty.