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The present paper attempts to explain the impact of debt diversification and various debt financing sources on firm value. The paper also aims to address the long-run causality of various factors affecting firm value.

The study employs a dynamic panel data model for a sample of 233 listed firms from 2010 to 2019. Two-step generalized method of moments (GMM) is devised to study the impact of firm-specific factors on firm value.

The study establishes a negative impact of debt diversification on firm value. Further, the results also signal how the choice of debt instruments has a heterogeneous effect on firm value. Non-bank debt leads to a discount in firm value, while bank debt has no effect on firm value. The long-run determinants of firm value are debt ratio, tangibility and liquidity.

The findings of the study would aid the mangers in making informed decisions regarding the debt financing structure. Too much reliance on non-bank debt instruments leads to a negative impact on firm value. Therefore careful evaluation is necessary before accessing multiple debt sources.

Debt heterogeneity is globally established; however, its presence in the Indian context has not been validated extensively. The study not only validates the existence of debt diversification but also investigates how individual debt instruments affect firm value that is yet to be examined in the Indian context.

The purpose of this paper is to investigate the increasing demand for corporate liquidity and examines the various factors influencing the cash position of firms in India. The financial policy to hold cash gained impetus after the financial crisis when the companies faced a severe cash crunch. However, the firms operating in emerging nations have an imperfect market mechanism with stringent regulatory norms. Thus, this paper attempts to examine the determinants of corporate cash holdings in an emerging country like India.

The paper focuses on the impact of various factors (leverage, firm size, profitability, growth along with other variables), on the cash structure of all the manufacturing companies listed on the Bombay stock exchange. The study employs panel data methodologies over a sample of 323 firms over a period of eight years from 2010 to 2017.

Significant estimators affecting cash holdings of a firm are the size of a firm, debt levels, tangibility, sales growth and research and development expense. Overall, the study finds evidence on the existence of Pecking Order theory in explaining the determinants of cash holdings in the Indian market.

The study attempts to explore the critical determinants of cash in the Indian context which can be useful for managers and academicians to understand how the key theories of cash holdings operate in an emerging economy like India.

India is an emerging economy and has recently gained global attention and has become a hotspot for foreign investments. Thus, this paper explores pieces of evidence on the critical factors affecting cash holdings in India. The study would provide an understanding of the existing cash policy in the Indian context and attempts to find the changes in the financing structure adopted by the manufacturing industry in the given period.

The purpose of this paper is to develop an efficient numerical scheme for non-linear two-dimensional (2D) parabolic partial differential equations using modified bi-cubic B-spline functions. As a test case, method has been applied successfully to 2D Burgers equations.

The scheme is based on collocation of modified bi-cubic B-Spline functions. The authors used these functions for space variable and for its derivatives. Collocation form of the partial differential equation results into system of first-order ordinary differential equations (ODEs). The obtained system of ODEs has been solved by strong stability preserving Runge-Kutta method. The computational complexity of the method is O(p log(p)), where p denotes total number of mesh points.

Obtained numerical solutions are better than those available in literature. Ease of implementation and very small size of computational work are two major advantages of the present method. Moreover, this method provides approximate solutions not only at the grid points but also at any point in the solution domain.

First time, modified bi-cubic B-spline functions have been applied to non-linear 2D parabolic partial differential equations. Efficiency of the proposed method has been confirmed with numerical experiments. The authors conclude that the method provides convergent approximations and handles the equations very well in different cases.

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.

Enzymatic desizing using α-amylase is the conventional and eco-friendly method of removing starch based size. Conventionally, enzymes are drained after completion of process; being catalysts, they retain their activity after reaction and need to be reused. Immobilization allows the recovery of enzymes to use them as realistic biocatalyst. This study aims to recover and reuse of α-amylase for desizing of cotton via immobilization.

This paper investigates the application of α-amylase immobilized on Chitosan and Eudragit S-100 for cotton fabric desizing. A commercial α-amylase was immobilized on reversibly soluble-insoluble polymers to work out with inherent problems of heterogeneous reaction media. The immobilization process was optimized for maximum conjugate activity, and immobilized amylases were applied for grey cotton fabric desizing.

The desizing performance of immobilized amylases was evaluated in terms of starch removal and was compared to free enzyme. The immobilized amylases showed adequate desizing efficiency up to four cycles of use and were recovered easily at the end of each cycle. The amylase immobilized on Eudragit is more efficient for a particular concentration than chitosan.

Immobilization associates with insolubility and increased size of enzymes which lead to poor interactions and limited diffusion especially in textiles where enzymes have to act on macromolecular substrates (heterogeneous media). The selection of support materials plays a significant role in this constraint.

The commercial α-amylase was covalently immobilized on smart polymers for cotton fabric desizing. The target was to achieve immobilized amylase with maximum conjugate activity and limited constraints. The reversibly soluble-insoluble polymers support provide easy recovery with efficient desizing results in heterogeneous reaction media.

This study aims to examine the research that examines psychological empowerment (PE) and employee engagement (EE) via bibliometric analysis. The study also aims to offer an overview of the present state of research and indicate potential future research topics.

The literature on PE and engagement was reviewed using bibliometric analysis based on publications in the Scopus database. The analysis comprises a three-field plot, theoretical framework examination, thematic analysis and quantitative analysis of the most frequently referenced publications, affiliations, countries and authors.

The study identifies research trends such as the use of the leadership lens, the examination of the different degrees of empowerment, the examination of alternate mechanisms to improve engagement and the impact of supervisor resources on these constructs. The study also suggests areas for future research, such as the influence of leadership and organizational culture on these two factors, the link between PE and EE and the impact of the changing structure of work via the increased use of technology and new work relations like gig work on these concepts.

This study offers a thorough and systematic overview of the state of the research in the area of PE and EE. This study emphasizes the significance of PE and engagement in management by giving a thorough overview of the present state of research and outlining future research possibilities.

This study aims at identifying critical success factors of a sustainable mobile banking application using text mining approach.

A total of 6,073 consumer reviews relating to a mobile banking application were collected and analyzed to meet the study objective. Latent Semantic Analysis (LSA) was done to identify the critical success factors of a sustainable mobile banking application.

The results indicated that privacy and security, navigation, customer support, convenience and efficiency are the key factors.

The study findings enrich the mobile banking and sustainable service delivery channel literature.

The results are expected to benefit the bankers in delivering effective banking services through a mobile banking application.

Studies in the sustainability are few yet promising particularly the ones that use rigorous statistics suitable on thousands of data points to accomplish the study objectives.

The manufacturing industry is presently experiencing technological disruption on a global scale. Consequently, to tackle such disruption, firms are identifying a volatile, uncertain, complex and ambiguous (VUCA) scenario and seeking ways to counter it. Accordingly, this paper aims to investigate the employee performance through assessing organizational citizenship behaviour (OCB) among the shop floor employees of the fast-moving consumer goods (FMCG) industry where a high-performance work system (HPWS) has been implemented.

A descriptive research design was used in the study, and 395 shop floor employees working in leading multinational firms, with a minimum global turnover of US$1bn, were interviewed. These manufacturing firms were located in three industrial clusters in the northern part of India.

The results indicate that HPWS influences OCB. Most of the dimensions of HPWS and OCB were found to be positively associated. The findings also disprove the labour process theory in the context of the study.

The findings report a broad view of the relationship between HPWS and OCB in the Indian manufacturing context. The study offers the practical insights that HPWS is a universally accepted framework and that organizations should focus on the effective implementation of HPWS in a VUCA scenario, which is in line with past studies. The study also provides future directions for research.

This paper has established the relationship between HPWS and OCB in the manufacturing sector, especially for shop floor employees.

We explore the skills required for digital leadership for reshaping existing business models toward digital models. Digital leadership is pivotal in gaining a competitive advantage and achieving successful digital transformation. However, little is known with regard to the underlying mechanisms related to digital leadership and transformation.

Data are collected through semi-structured interviews involving 20 participants from five Pakistani textile companies. Thematic analysis was employed as a data analysis tool.

Findings show that certain skills such as technological know-how, innovativeness, adaptability, ability to lead and steer, honesty, integrity, transformative vision, communication and collaboration are conducive to successful digital transformation in textile manufacturing firms. Similarly, digital leaders can significantly enhance business model innovation, create value for the firm, help develop new products (value proposition) and create Ecosystem partnerships (value network).

This article bridges gaps between existing literature on digital transformation and leadership. Digital leadership skills for digital transformation and the role of digital leaders in business model innovation have not been explored before. The conceptual framework is put forth, propositions are proposed and the findings offer some future research directions.