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The purpose of this paper is to examine the optimal leverage ratio, speed of adjustment, and which factors contribute to achieving the target of selected telecom companies in a partial adjustment framework from 2008 to 2017. Further is to analyze the likelihood of bankruptcy of sample companies by Altman Z-Score model and to suggest which theory of capitals structure is better in explaining leverage strategies and judicious mix of debt and equity structure of the selected telecom companies.

This paper chooses a partial adjustment model and uses the generalized method of moments technique to identify the variables that influence the target leverage ratio and the factors that influence the speed at which the target leverage is adjusted. Second, the Altman Z-score model is used in this paper to research the financial status of telecom companies using financial instruments and techniques.

For Indian telecom firms, firm-specific variables such as profitability, NDTS and Z-score lead to greater debt adjustment towards optimal level target leverage. The paper also highlights new paradigms in the Indian telecom sector, stating that top market leaders such as Bharti Airtel, BSNL, Idea, Vodafone and R.com, among others, should focus on debt reduction and interest payments, as well as implement new strategies to solve the crisis and change financial policies.

It mainly focuses on firm-specific variables because the firm-specific variables affect the leverage framework. The country-specific variables are not taken into the study. These results may be unique to telecom companies due to some peculiarities existing in the telecom sector in India. Although other sectors, both national and international level, can be taken into consideration.

This paper has ramifications for corporate executives, investors and policymakers in India, for example, in terms of considering different transition costs while changing a telecom company’s financing decisions.

To the best of the authors’ knowledge, this is the first paper of its kind to look at both financial and econometric tools to assess financial performance using the Altman Z-Score model, as well as decide leverage strategies and the pace with which they can be adjusted to target leverage in the context of Indian telecom companies.

This study aims to understand how quickly Japanese banks readjust their capital ratios (leverage, regulatory capital, tier-I capital and common equity) following an economic shock.

This study uses a two-step system GMM framework to test the study's hypotheses using the annual data of Japanese commercial and cooperative banks ranging from 2005 to 2020.

The findings show that banks adjust their leverage ratio faster than regulatory capital, tier-I capital and common equity ratios. In addition to that, the results reveal that the speed of capital adjustment is higher for commercial banks than for cooperative banks, suggesting higher economic costs and implications for commercial banks. Furthermore, it is worth noting that well-capitalised (under-capitalised) banks tend to prioritise the adjustments to common equity (leverage) before considering the adjustments to leverage (common equity). According to the results, high-liquid (low-liquid) banks alter their regulatory capital and tier-I capital ratios (leverage) more quickly (more slowly) than low-liquid (high-liquid) banks.

The findings suggest that when formulating and implementing new banking regulations, particularly in assessing and adjusting specific capital requirements under Pillar II of Basel III, management (including bankers, regulators and policymakers) should consider the heterogeneity observed in the rate of capital adjustment across various bank characteristics. Additionally, bank managers should also consider the speed of adjustment when determining optimal half-life and target capital structures.

To the author's knowledge, this study represents a pioneering investigation into the rate of adjustment of capital ratios (leverage, regulatory, tier-I and common equity) within Japan's banking sector. The study employs a comprehensive dataset encompassing both commercial and cooperative banks to facilitate this analysis. A notable contribution to the existing body of literature, this study offers a detailed analysis and emphasises the varying degrees of adjustment in capital ratios. The study also highlights the heterogeneous nature of the adjustment rate in these ratios by categorising the data into well-capitalised, under-capitalised, highly liquid and low-liquid banks.

This paper aims to theorize that if risk affects costs and benefits of capital structure adjustments, then it should affect the speed at which firms adjust their leverage toward the target. To investigate this hypothesis, the author empirically examines the role of firm-specific and macroeconomic risk on firms’ capital structure adjustments.

The author augments the standard reduced-form partial adjustment model of capital structure by incorporating firm-specific and macroeconomic risk. The two-step robust system-generalized method of moments (GMM) estimator is used to estimate the proposed model for a large panel of UK manufacturing firms. An unbalanced annual panel data set covering the period from 1981 to 2009 is utilized for empirical analysis.

The estimated adjustment speeds indicate that both firm-specific risk and macroeconomic risk significantly affect the speed at which firms adjust their capital structure toward the target. In particular, the author shows that firms adjust their leverage faster toward the target when firm-specific risk is relatively low. This is perhaps because firms face lower costs of adjustment when both firm-specific and macroeconomic risks are low. Overall, the paper provides evidence that different levels and different types of risk exert asymmetric effects on capital structure adjustments.

The results presented in this paper suggest that managers have to carefully consider both the overall state of the economy and the solvency of their own business activities when making their financing decisions. The results also help in explaining why firms time equity and debt markets.

The paper significantly adds to our understanding of asymmetries in adjustment speed across firms and over times. The paper can also be useful to understand why firms would not aggressively act to offset the effects of changes in the market value of equity or gains and losses in earnings.

In order to improve banks' ability to fight against risks, China's financial regulatory authorities refer to the Basel Accord, and bank capital adequacy ratio is taken as an important means of control. The purpose of this paper is to investigate the internal mechanism between capital buffers and risk adjustment.

Based on the dynamic characteristics of a bank's continuing operations, the authors established an unbalanced panel of China's commercial bank balance‐sheet data from 1991 to 2009 and used the Generalized Method of Moments to examine the relationship between short‐term capital buffer and portfolio risk adjustments.

The authors' estimations show that the relationship between capital and risk adjustments for well capitalized banks is positive, indicating that they maintain their target level of capital by increasing (decreasing) risk when capital increases (decreases). In contrast, for banks with capital buffers approaching the minimum capital requirement, the relationship between adjustments in capital and risk is negative. That is, low capital banks either increase their buffers by reducing their risk, or gamble for resurrection by taking more risk as a means to rebuild the buffer. Moreover, the authors' estimations show that the management of short‐term adjustments in capital and risk is dependent on the size of the capital buffer.

From the current research documents, there are few empirical researches on capital buffers and risk adjustment, and the research sample time limits of current papers are a little earlier. The researches did not reflect China's commercial banks' capital buffer and risk adjustment after the new Basel Accord.

Banks' adjustment speed of target level depends on the size of capital buffer, proving that the speed of adjusting capital buffer of banks with smaller capital buffer is significantly faster than their counterparts with larger capital buffers.

The paper uses the dynamic feature of banks' lasting operations as the logical starting point, which is ignored by the current researches, and investigates the internal mechanism between capital buffers and risk adjustment.

The study examines the existence of target level of working capital and the speed of adjustment toward the target for eight manufacturing sectors of Indian economy. In addition, this study examines the impact of financial constraints on the speed of adjustment.

This study is based on secondary financial data of 1936 Indian manufacturing companies from eight sectors for a period of 18 years (2000–2018). This study employs two-step GMM techniques to arrive at results.

Results of the study confirm that firms do have target working capital, but the speed of adjustment from the current level of working capital to the target working capital is slow, and the speed of adjustment varies across sub-sectors. Moreover, we found that firms that are likely to be less constrained adjust their working capital quickly compared to firms facing high financial constraints.

This study contributes to working capital management literature by examining the speed with which the firms move toward their target and also the impact of financial constraints on the speed of adjustment across eight manufacturing sectors of Indian economy. Further, the study examines the impact of financial constraints on the speed of adjustment.

This paper aims to conduct bibliometric analysis on the studies dealing with capital structure’s speed of adjustment (SoA) and identify the prominent themes while suggesting future research directions in the area. The existing reviews broadly focus on the capital structure, which provides the scope for conducting a review on this sub-aspect of capital structure.

This study uses a three-stage process to conduct this review: identification of academic journals, selection and analysis of target papers. This study uses a combination of bibliometric tools and a system thinking approach to assess the current status of publications and emerging themes within the literature.

This study has found a progressive evolution of SoA in capital structure research from 1984 to 2021. Studies largely focus on implementing the dynamic models to analyse the impact of adjustment costs, dynamic economic conditions, corporate governance practices and other variables on the firms’ adjustment speed and financial decisions. The network analysis of citations, keywords and clusters gives further knowledge on the intellectual structure of the data.

This study is highly dependent on the papers available within the SCOPUS database. Studies not included herein are not part of this analysis, which may or may not bear an effect on the study’s findings.

To the best of the authors’ knowledge, the application of systems engineering concept of “system thinking approach” to identify literature gap and suggest directions for forthcoming research is the first of its kind, thus adding a novel and multidisciplinary aspect to this study.

This paper seeks to analyze the family firm's capital structure decisions, focusing on the speed of adjustment (SOA) as well as on the effect of distance from the target capital structure on the SOA towards target short-term and long-term debt ratios in unlisted small and medium-sized family firms.

Methodologically, we use dynamic panel data estimators to estimate the effects of distance on the speeds of adjustment towards those targets. Data for the period 2006–2014 were collected for two research sub-samples: one sub-sample with 398 family firms; the other sub-sample contains 217 non-family firms.

The results show that the deviation from the target debt ratios impacts negatively on the speeds of adjustment towards target short-term and long-term debt ratios in unlisted family firms. These results suggest that family firms, deviating from target debt ratios, face deviation costs, i.e. insolvency costs, inferior to the adjustment costs, i.e. transaction costs. Therefore, family firms stay away from the target debt ratios for a long time than do non-family firms.

The research sample comprises a low number of family firms, therefore for future research we suggest increasing the size of the sample of family firms to get a deeper understanding of family firms' SOA towards capital structure. Additionally, we suggest the analysis of other potential determinants of the speed of adjustment towards target capital structure.

The results obtained suggest that the distance from the target short-term and long-term debt ratios can be avoided if these firms do not depend almost exclusively on internal finance to adjust towards target capital structure. Moreover, for policymakers, we suggest the creation/promotion of alternative external finance sources, allowing reduced transaction costs that contribute to a faster adjustment of small family firms towards target capital structure.

The most previous research focusing on capital structure decisions have focused on listed family firms. To fill this gap, this study examines the speed of adjustment towards target debt ratios in the context of unlisted family firms. Moreover, transaction costs are a function of debt maturity, therefore this study examines separately the speeds of adjustment towards target short-term and long-term debt ratios. This paper shows that the adjustment costs (i.e. transaction costs) could hold back family firms from rebalancing its capital structure.

The purpose of this paper is to examine the role of institutional, macroeconomic, industry, and firm characteristics on the adjustment speed of corporate capital structure within the context of developing countries.

The authors considers a sample of 986 firms drawn from nine developing countries in Africa over a period of ten years (1999-2008). The study develops dynamic partial adjustment models that link capital structure adjustment speed and institutional, macroeconomic, and firm characteristics. The analysis is carried out using system Generalized Method of Moments procedure which is robust to data heterogeneity and endogeneity problems.

The paper finds that firms in developing countries do temporarily deviate from (and partially adjust to) their target capital structures. Our results also indicate that: more profitable firms tend to rapidly adjust their capital structures than less profitable firms; the effects of firm size, growth opportunities, and the gap between observed and target leverage ratios on adjustment speed are functions of how one measures capital structure; and adjustment speed tends to be faster for firms in industries that have relatively higher risk and countries with common law tradition, less developed stock markets, lower income, and weaker creditor rights protection.

Future research should focus on examination of the adjustment speed of debt maturity structure. Identification of industry-specific characteristics that affect the pace with which firms adjust their capital structure to the optimum is another possible avenue for future research.

Our findings have practical implications for corporate managers, governments, legislators, and policymakers.

The study focuses on firms in developing countries for which the literature on adjustment speed of capital structure is virtually non-existent. Furthermore, unlike previous works on capital structure, it explicitly models industry variable as one of the determinants of adjustment speed. Therefore, it contributes to the literature on capital structure and adjustment speed in general and to the literature on developing countries in particular.

The purpose of this paper is to study the dynamics of capital structure in the context of Indian manufacturing companies in a partial‐adjustment framework during the period 1993‐1994 to 2007‐2008.

This paper specifies a partial‐adjustment model and uses the generalized method of moments technique to determine the variables which affect the target capital structure and to find out the factors affecting the adjustment speed to target capital structure.

Firm‐specific variables like size, tangibility, profitability and market‐to‐book ratio were found to be the most important variables which determine the target capital structure across the book and market leverage and the factors like size of the company, growth opportunity and the distance between the target and observed leverage determine the speed of adjustment to target leverage for the Indian manufacturing companies.

The behavioural variables like managers' confidence and attitude towards raising the external finance have not been incorporated in the model to determine the target capital structure due to the data constraint.

This paper has implications for corporate managers in India, for example, to consider the various adjustment costs while altering the financing decisions of the company with other variables like flexibility of the manager, direct cost of debt and equity.

This paper is first of its kind to study both the determination of target capital structure and the speed of adjustment to target capital structure in the context of Indian companies.

The purpose of this paper is to explore the psychological adjustment process of expatriates from Chinese multinational enterprises, including how their social capital affects this process.

This qualitative investigation was based on semi-structured, in-depth interviews with 26 Chinese expatriates. The grounded theory method was applied to guide the data collection and analysis.

The psychological adjustment process of Chinese expatriates includes three periods: crisis, self-adjustment and self-growth period. In addition, bonding capital (including organizational, family and co-cultural colleagues’ support) is more conducive to Chinese expatriates’ psychological well-being than bridging capital (e.g. host-nationals’ support). Finally, a separation acculturation strategy is more conducive to psychological adjustment, rather than an integration strategy.

This study focused on expatriates themselves. Future research should consider other stakeholders (e.g. organizations, family), and examine expatriate adjustment from new perspectives (e.g. strategic human resource management, work-family balance). This study had a small sample and focused on only one organization. Future research could usefully add other Chinese multinational corporations, and other Chinese expatriates to expand the generalizability of the current findings.

This study suggests the possible benefits of management practices for expatriates. Organizations can develop an “expatriate bubble” to help structure basic life overseas. Organizations could develop family-support programs and make them expatriate-supportive. Organizations should also strengthen the connections between expatriates and local colleagues.

Few scholars have elaborated on how different support groups (based on their cultural backgrounds) influence the psychological adjustment of expatriates. Until now, mainland Chinese expatriates have received little attention. In addition, this research takes a significant step forward by illuminating the psychological adjustment of Chinese expatriates from a social capital perspective.