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The purpose of this paper is to investigate the relationship between dividend policy and the life cycle of firms in India. In addition, this study intends to examine the variation in dividend behaviour over the life cycle of a firm. The study anticipates that a firm's dividend behaviour varies over its life cycle.

To scrutinize the validity of the proposition, the authors classify 1968 non-financial industrial firms listed at Bombay Stock Exchange (BSE) into growth, mature and stagnant firms over the period 2000–20. Additionally, to check the robustness of the results, they use an array of techniques such as analysis of variance, pooled ordinary least squares, fixed effects models and random effects models.

The empirical findings suggest that dividend behaviour varies over a firm's life cycle. Specifically, stagnant firms are paying significantly higher dividends than growth firms. Mature firms are paying significantly higher dividends than growth firms. The results are consistent after controlling the effects of firm's size, profitability, leverage, operating risk, systematic risk and growth opportunities.

The findings are useful for corporate decision makers in establishing an appropriate dividend policy conditional on firms' life cycle stage and for shareholders in making investment decisions.

The relation between dividend policy and firm life cycle has not been examined before in the context of Indian stock market. Thus, this research bridges this gap in the literature.

Recently, there has been a shift toward the embodied energy assessment of buildings. However, the impact of material service life on the life-cycle embodied energy has received little attention. We aimed to address this knowledge gap, particularly in the context of the UAE and investigated the embodied energy associated with the use of concrete and other materials commonly used in residential buildings in the hot desert climate of the UAE.

Using input–output based hybrid analysis, we quantified the life-cycle embodied energy of a villa in the UAE with over 50 years of building life using the average, minimum, and maximum material service life values. Mathematical calculations were performed using MS Excel, and a detailed bill of quantities with >170 building materials and components of the villa were used for investigation.

For the base case, the initial embodied energy was 57% (7390.5 GJ), whereas the recurrent embodied energy was 43% (5,690 GJ) of the life-cycle embodied energy based on average material service life values. The proportion of the recurrent embodied energy with minimum material service life values was increased to 68% of the life-cycle embodied energy, while it dropped to 15% with maximum material service life values.

The findings provide new data to guide building construction in the UAE and show that recurrent embodied energy contributes significantly to life-cycle energy demand. Further, the study of material service life variations provides deeper insights into future building material specifications and management considerations for building maintenance.

Drawing on the resource-based view (RBV), this study investigates how tax planning affects the likelihood of financial default in different stages of the corporate life cycle.

Collecting a large sample of US firms between 1989 and 2016, hypotheses are tested using a hazard model. Several robustness and endogeneity checks corroborate the main findings.

The results show that tax-planning firms are less likely to default in the introduction and decline stages, while they are more likely to default in the growth and maturity stages. The findings suggest that introductory and declining firms use cash resources obtained from tax planning efficiently to meet their needs and acquire other useful resources. In growing and mature firms, tax aggressiveness generates unnecessary slack resources, weakens managerial discipline and increases reputational risks.

The results shed light on the benefits and costs associated with tax planning throughout firms' life cycle, holding great significance for managers, investors, lenders and other stakeholders.

This study contributes to the literature that examines resource management at different life cycle stages by showing that cash resources from tax planning are managed in distinctive ways in each life cycle stage, having a varied impact on the likelihood of default. The authors shed light on underexplored cash resources. Furthermore, this study shows the potential linkages between the agency theory and RBV.

The study examines the influence of a firm's life cycle on the cash flow classification of Indian firms.

The study employs Dickinson's (2011) cash flow patterns to classify firm years under various life-cycle stages. Cash flow classification is employed to measure a firm's classification shifting (CS) practices. The study includes Indian firms listed on the Bombay Stock Exchange during 2012–2020, an ordinary least squares regression model, a fixed-effect model and a panel corrected with standard error regression method.

Firms face different opportunities and challenges at different stages of the firm's life cycle and therefore adopt cash flow CS. The results show that firms adopt cash flow CS during introduction, growth and decline stage of life cycle either to boost or to reduce operating cash flows.

This study is one of its kind to study the influence of a firm's life cycle on the cash flow classification of Indian firms.

The purpose of this paper is to propose a disruption claim management (DCM) life cycle and a risk management framework to provide comprehensive guidance to construction practitioners for facilitating effective and efficient DCM.

DCM life cycle was initially developed through a focus group discussion (FGD) with the participation of the construction practitioners who have diverse experiences about DCM. The life cycle is comprised of 6 phases and also includes proper reactions of the owners and contractors. Then, 42 risk factors that can impact the deliverables of DCM were identified through a literature review and an additional FGD session. This was then followed by a Fuzzy Analytical Hierarchy Process (FAHP) which was performed to evaluate the importance of each risk factor in terms of the factor's impact on the success of DCM. Additionally, consistency analysis was performed to further maximize the reliability of the results.

Findings revealed that a proactive and systematic approach should be adopted and DCM practices should be initiated before any disruption event is triggered. Accordingly, the proposed framework recommends DCM practices to be initiated early in the contract development phase since compensation for the disruption might be recovered only to the extent that the contract permits. The contract-related risks were given top priority by the experts so that the results of the fuzzy AHP analysis also verified the significance of the contract development phase. Besides contract-related risks, risks related to insufficient site observation, ignorance of the project team, cognitive bias and conflict of interest were determined as the most significant DCM risks, needing an urgent and sophisticated risk response plan. Lastly, results suggested that “Site observation and record-keeping” is the most formidable phase since the phase's implementation on a continuous basis could create unforeseen organizational challenges such as mismanagement of project records, especially in the dynamic and turbulent environment of the construction projects.

Disruption – which is caused mostly by change – is inevitable in construction projects due to their sophisticated nature. DCM, therefore, becomes crucial to compensate losses of contractors and eliminate or diminish the prolonged dispute resolution process. Existing studies, however, do not provide a comprehensive theoretical basis for the DCM life cycle and DCM life cycle's potential risks so that DCM life cycle's promising benefits can hardly be materialized. Thus, developing a DCM life cycle and associating DCM life cycle with risk management, this study is highly believed to make a promising theoretical contribution to the DCM domain since this is one of the earliest attempts in the literature. Additionally, this research provides construction practitioners with an insight into the effective implementation of DCM practices in construction projects.

The purpose of this paper is to investigate the impact of intellectual capital (IC) and its components (human, structural, relational and innovation capitals) on financial performance (FP) at different life cycle stages.

The study uses the data from Chinese manufacturing listed companies during 2014–2018. The modified value added intellectual coefficient (MVAIC) model is employed as the measurement of IC efficiency. Finally, multiple regression analysis is used to test the research hypotheses.

This study shows that the impact of IC on FP is different across life cycle stages. Specifically, at the birth stage, human capital (HC), structural capital (SC) and innovation capital (INC) have a positive impact on FP. At the growth and mature stages, all IC components contribute to FP improvement. HC and SC play an important role at the revival stage, while only HC positively affects FP at the decline stage.

The findings may help corporate managers to make optimal strategies to improve FP by effective utilization of IC resources in the complex and competitive business environment. Meanwhile, companies can invest in the core elements of IC at different stages of development, so as to maximize the contribution of IC to company value.

This is among the few studies to explore the impact of IC on FP of manufacturing listed companies in the Chinese context from the perspective of life cycle. It also makes novel contributions in measuring IC by the MVAIC model with the inclusion of relational capital and INC that are largely neglected in previous research.

This paper bridges the gap between the theory and practice by developing a life cycle sustainability tracker (LCST). The study is seeking to proffer solutions to an observed shortcoming of conventional life cycle sustainability assessment (LCSA) communication platforms. Notably, the static nature of the information provided on such platforms has made it difficult for them to be used for real-time decision-making and predictions. The main aim of this paper is to develop a LCST that facilitates a dynamic visualisation of life cycle sustainability results and allows for an integrated benchmark across the dimensions of sustainability.

The study leverages the model development capabilities of the design science research strategy in accomplishing a dynamic and novel communication platform. A life cycle thinking methodology and appropriate multicriteria decision approach (MCDA) is applied to accomplish a comprehensive, streamlined and replicable approach in mapping and tracking the progress of sustainable development goals (SDGs) in the National Infrastructure Pipeline (NIP) projects in India.

It was found that: (1) The use of the LCST tracker provides a dynamic and holistic insight into the key LCSA indicators with clearly defined benchmarks to assess the impact on the SDG 11, (2) The NIP projects achieve an upward trend across all the regions, and the percentage of opportunities ranges from 11 to 24%, with the South experiencing the highest growth and the North having the minimal increase in percentage and (3) The assessment score (52–58%) provides performance metrics that align well with the LCST – which ranges between “Fair” and “Average” for all the regions in India.

The novelty of this research is that the LCST provides a transparent and harmonised approach to reporting on the LCSA results. The LCST utilises heat maps and radial mapping to achieve an intuitive display of large amounts of highly heterogeneous data, thus allowing the synthesis of large sets of information compactly and with coherence. Progress towards the SDGs change on a yearly basis; hence, a dynamic LCSA tool provides a timely and the valuable context to map and track performance across different regions and contexts.

This study aims to examine the role of the board of directors in affecting earnings management practices across small- and medium-sized enterprises (SMEs) life cycle.

Data is collected from 280 SMEs listed on the London Stock Exchange during the period of 2009–2016. Fixed effects regression analysis is used to test the hypotheses.

This study shows that the impact of the board of directors' roles on earnings management practices varies depending on the SMEs life cycle stage. In the introduction, growth and decline stages of SMEs, the wealth creation role of the board is negatively significant with earnings management, while the wealth protection role of the board is positively significant in the growth and maturity phases. Results suggest that the board's responsibility to create wealth deters early-stage earnings management strategies, while protecting shareholder interests, in latter stages, leads to a decrease in earnings management.

The findings suggest that corporate governance should be customized to the specific stage of the SMEs life cycle. Additionally, different life cycle stages may impose different requirements on corporate boards to shape the effectiveness of these mechanisms and constrain earnings management practices.

To the best of the authors’ knowledge, this study offers one of the first insights on the UK SMEs to understand how board functions and earnings management practices vary over SMEs life cycles. It will offer important information on the effect of board features on earnings management in SMEs in the UK and is anticipated to be of importance to policymakers, regulators, investors and practitioners.

Starting with the notion that each building has an overall life cycle, the paper uses building-based and investment-based life cycles to identify likely decision points for renovations, including sustainability enhancements, and identifies patterns in sustainability decisions.

This real estate insights paper considers how commercial real estate and the built environment it creates, owns and manages impacts the sustainability of urban areas and the globe. By combining building-based and investment-based life cycles, it is possible to develop a unique “sustainability enhancement quotient” for individual buildings and the built environment for an urban area over a given time interval.

Using two life cycles allows the identification and likelihood of sustainability decision points. The same life cycles and decision points are used to consider the likely extent of such renovations. This is in addition to continuous consideration of renovations producing economic benefits in the form of lower operating costs and quick return of capital.

Useful for investment decision-making and policy design and implementation.

This is a useful tool for public and private decision making. It is suggested that the sustainability enhancement quotient may be used to design and implement policies and decisions maximising the likelihood of sustainability enhancement in an urban area's built environment.

Provides a framework for more effective sustainability decisions and public policy. The public-private interplay inherent in every building is emphasised throughout.

Original combination of existing tools.

Scholars mainly propose and establish theoretical models of cumulative fatigue damage for their research fields. This review aims to select the applicable model from many fatigue damage models according to the actual situation. However, relatively few models can be generally accepted and widely used.

This review introduces the development of cumulative damage theory. Then, several typical models are selected from linear and nonlinear cumulative damage models to perform data analyses and obtain the fatigue life for the metal.

Considering the energy law and strength degradation, the nonlinear fatigue cumulative damage model can better reflect the fatigue damage under constant and multi-stage variable amplitude loading. In the following research, the complex uncertainty of the model in the fatigue damage process can be considered, as well as the combination of advanced machine learning techniques to reduce the prediction error.

This review compares the advantages and disadvantages of various mainstream cumulative damage research methods. It provides a reference for further research into the theories of cumulative fatigue damage.