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Interest rate derivatives (IRDs) are the essential components of financial risk management and are used across various industry sectors. The objective is to analyze the differences in approach to managing interest rate risks between the Indian corporates that execute IRDs and the ones that do not.

Interest rate fluctuations require Indian corporates to hedge their exposures in foreign currency interest rates. This is all the more true for mid-sized corporates because of their balance sheet exposures. Additionally, they may not have the resources to formulate risk management policies. This paper analyzes data collected from financial statements of a diverse set of companies that use IRD and helps in formulating such a strategy.

The results indicate significant differences for some of the parameters like information asymmetry and agency cost between users and non-users of IRDs. The study further suggests causality between users of derivatives and parameters like size, growth and debt.

The study compares users and non-users of IRDs, thereby identifying factors unique to users of IRDs. It also studies causality relations which explain the motivation to do IRDs. Thus, it enables risk managers to use this as a reference point to decide on their strategies.

While there are multiple studies across geographies and sectors including commercial banks in India on the usage of interest rate swaps, this study focuses on Indian mid-tier corporates. Furthermore, the study distinguishes between users and non-users based on financial parameters, which in turn would provide a framework for decision-hedging strategies.

This study aims to add to the growing literature on the trade–finance nexus by exploring the interplay between a country's level of financial development, the external finance dependence of firms and their exporting decisions.

The study first develops a theoretical model to motivate the idea that a firm's liquidity (financial) position and its home country's level of financial development act as substitute factors in its export market entry decisions. It then empirically tests whether an improvement in a country's financial development level enhances the number of entrants in the foreign markets and boosts the exports of incumbent exporters using firm-level data of manufacturing firms in India for the period 1993–2020.

Empirical results suggest that a higher level of financial development helps increase the exporting probability of firms that rely more on external finance for their operations. Further, the study finds that the sunk costs-induced hysteresis effect plays a major role in firms' exporting decisions and financial factors don't play a significant role in the exporting activities of incumbent exporters.

The findings suggest that a well-developed financial market is necessary to help more and more firms initiate their foreign market operations. The results underscore that trade-liberalisation measures alone may not increase India's exports and the government must complement them with financial sector reforms.

Studies highlighting the role of financial sector development in helping financially-constrained Indian firms overcome the entry barriers associated with exporting are extremely limited. This study contributes to this nascent literature by conducting an empirical investigation on an extensive database of Indian manufacturing firms. Moreover, in contrast to the previous firm-level studies in this area, this empirical analysis uses the actual values of external finance raised by the firms as a critical factor in determining their extensive and intensive margin of exports instead of the usual balance sheet variables such as liquidity and leverage.

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural relationships among each other. The purpose of this study is, therefore, to establish the complex structural relationships of risks involved.

In total, 76 published articles from the previous literature are reviewed using the content analysis method. Three risk networks in different phases of power plant projects are depicted based on literature review and case studies. The possible methods of solving these risk networks are also discussed.

The study finds critical cost overrun risks and develops risk networks for the procurement, civil and mechanical works of power plant projects. It identifies potential models to assess cost overrun risks based on the developed risk networks. The literature review also revealed some research gaps in the cost overrun risk management of power plants and similar infrastructure projects.

This study will assist project risk managers to understand the potential risks and their relationships to prevent and mitigate cost overruns for future power plant projects. It will also facilitate decision-makers developing a risk management framework and controlling projects’ cost overruns.

The study presents conceptual risk networks in different phases of power plant projects for comprehending the root causes of cost overruns. A comparative discussion of the relevant models available in the literature is presented, where their potential applications, limitations and further improvement areas are discussed to solve the developed risk networks for modeling cost overrun risks.

The existing research on institutional distance implicitly posits the monotonic effect of contextual differences on the multinational enterprise (MNE) behaviors (e.g. entry mode, research and development (R&D) investment and subsidiary reverse knowledge transfer). Namely, MNEs from the same home to the same host countries are thought to have homogenous perceptions on the institutional influences and thus behave similarly. However, the authors argue that MNEs, due to their different performance aspirations in host countries, will have heterogenous perceptions on such contextual influences and thereafter behave differently.

Drawing on the behavioral theory of the firm and employing a unique sample comprised of 140 Chinese MNEs' foreign direct investments (FDIs) in Taiwan in 2017, the authors developed and tested the hypotheses.

The authors found that the emerging-market MNEs' (EMNEs’) perceptions of higher local institutional difficulties will be strengthened when their local performances are below their aspiration levels, making them more risk-taking. Nevertheless, EMNEs' local experiences and local equity-based partnerships will mitigate such negative perceptions, mitigating their risk-taking orientation.

The empirical findings make contributes to the international business (IB) literature by extending knowledge on the determinants and conditions of the heterogeneity in EMNEs' behavioral orientations when in face of the same institutional distance. The authors also provide managerial implications by showing that EMNEs' firm-specific resources (i.e. local experience and local equity-based partnership) will alter their perceptions of local institutional difficulties, leading to different behavioral orientations.

This study aims at proposing a hybrid model for early cost prediction of a construction project. Early cost prediction for a construction project is the basic approach to procure a project within a predefined budget. However, most of the projects routinely face the impact of cost overruns. Furthermore, conventional and manual cost computing techniques are hectic, time-consuming and error-prone. To deal with such challenges, soft computing techniques such as artificial neural networks (ANNs), fuzzy logic and genetic algorithms are applied in construction management. Each technique has its own constraints not only in terms of efficiency but also in terms of feasibility, practicability, reliability and environmental impacts. However, appropriate combination of the techniques improves the model owing to their inherent nature.

This paper proposes a hybrid model by combining machine learning (ML) techniques with ANN to accurately predict the cost of pile foundations. The parameters contributing toward the cost of pile foundations were collected from five different projects in India. Out of 180 collected data entries, 176 entries were finally used after data cleaning. About 70% of the final data were used for building the model and the remaining 30% were used for validation.

The proposed model is capable of predicting the pile foundation costs with an accuracy of 97.42%.

Although various cost estimation techniques are available, appropriate use and combination of various ML techniques aid in improving the prediction accuracy. The proposed model will be a value addition to cost estimation of pile foundations.

The purpose of this study is to systematically review available state-of-the-art literature on comparative studies on Quick Commerce (Q-commerce) and E-commerce and their greenhouse gas (GHG) emissions.

The literature survey methodology is based on the funneling approach of Kitchenham (2004), where results are obtained according to inclusion and exclusion criteria. The literature review methodology used for this study covers the period from 2016 to 2022. The areas considered for the survey are operations, logistics and supply chain network design for the distribution of goods in e-business. After deciding on the criteria, a total of 140 articles were extracted from 9 journal articles that study e-commerce and environmental emissions.

The result of this study reveals that GHG emissions from both modes of shopping depend on various parameters such as speed of delivery, last-mile depot locations, logistics and vehicle efficiency, customers’ order patterns and average basket size. Furthermore, the findings also highlight the difference between Q-commerce and E-commerce supply chain networks.

This study only accounts for GHG emissions from logistics activities, but there are other sources of GHG emissions in the overall supply chain that are not taken into consideration. Supply chain/business analysts in Q-commerce companies might refer the findings from this study to measure GHG emissions from their operations.

This is the first study in the Q-commerce field that uses a structured approach to find relevant literature from the years 2016 to 2022 and focuses on GHG emission measurement.

This paper aims to revisit the relationship between sales growth and profitability by exploring the direct and indirect effects of cost stickiness in the growth process. Cost stickiness refers to asymmetric variations of costs associated with increases and decreases in sales. Cost stickiness is analyzed as a strategic liability that negatively affects profitability because it contributes to organizational rigidity that causes opportunity costs.

The empirical design is based on a large sample of 65,599 French firms drawn from the Amadeus database and it covers the period 2010 to 2019. The authors take advantage of the presentation of expenses made by nature in Amadeus to calculate cost stickiness in a more direct way than what is commonly done in the literature. The authors use various regression models to test the hypotheses.

For firms that experience rapid growth in sales, cost stickiness has a positive moderating effect on the relation between sales growth and profitability because of a higher asset turnover efficiency. However, for firms that experience slow growth, no growth or a decrease in sales, cost stickiness plays a negative moderating effect on the relation between sales and profitability.

This work contributes to the discussion about the conditions under which high growth is associated with greater profitability and conceptualizes cost stickiness as a strategic liability. The empirical context, privately held firms, has been overlooked by previous research.

Traditional construction materials and methodologies are often perceived to be unproductive, labour-intensive and detrimental to the environment. Mass-engineered timber (MET) is a new structural material that is capable of overcoming numerous issues that otherwise affect the built environment. This study was formulated to assess the current attitude and perception of young Singaporeans towards the concept of Engineered Timber Residential Buildings (ETRBs).

The study employs the mixed-method approach. Questionnaires were used as the primary mode of data gathering. These were disseminated to Singaporeans between the age of 18 and 35 years. A total of 179 valid responses were gathered. Semi-structured interviews were subsequently conducted with six individuals with different demographics in order to gain further insightful opinions and to allow cross validation of responses.

Statistical analysis revealed that 80% of respondents were willing to accept ETRBs, but a lack of awareness and knowledge of MET and the presence of misconceptions, such as an association with deforestation, may present concerns. The study also revealed that individual acceptance of ETRBs is not affected by demographics.

The production of MET involves lower overall carbon emissions than that of conventional materials, and this also allows adoption of the Design for Manufacturing and Assembly (DfMA) concept and offers the benefit of carbon sequestration. Residential buildings are the second most common building type in Singapore; significant benefits can be gained if MET is used as the primary material for residential buildings. In general, young stakeholders in Singapore welcome the concept of ETRBs, despite possessing uncertainties about ETRBs—understandable given that the material lacks a track record of usage. Public authorities are thus advised to explore the feasibility of materialising the concept of ETRBs as an option for public housing.

The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

Prefabricated construction (PC) can benefit construction industry due to its high efficiency, energy saving, consumption reduction and safety. However, the high capital cost is a critical challenge hindering its development in China. The collaboration of PC stakeholders is conducive to improving cost management efficiency and optimizing resource allocation which has been ignored in previous studies. Therefore, this study aims to explore the collaboration paths of stakeholders in the process of solving critical cost influencing factors (CIFs) of PC to reduce costs.

Firstly, 25 CIFs and five main stakeholders that affect PC capital cost were identified through literature research and expert interviews. Then, questionnaires were used to investigate the relationship between stakeholders and CIFs from the perspectives of three stakeholder attributes of proximity, attitude and power, respectively. Finally, based on the survey data, three stakeholder-CIF networks from three attributes perspective and a comprehensive network were constructed and used for subsequent social network analysis.

(1) Stakeholders mainly show willingness and potential to collaborate on organization and management factors; (2) More stakeholders pay attention to incentive policies and the setting of prefabrication rates and assembly rates, while all stakeholders have the right to facilitate information and resource sharing in the PC supply chain; (3) The comprehensive network shows a core-periphery structure. As core stakeholders, contractor, designer and manufacturer are more likely to actively manage the 14 core CIFs.

This paper innovatively combined stakeholder and cost management in PC, and used two-mode network based on three stakeholder perspectives to reveal the collaboration potential and motivation of stakeholders in PC cost management. The findings not only provide guidance for stakeholders to find potential partners and optimize resource allocation in solving specific cost issues, but also facilitate stakeholders' sustainable collaboration to achieve PC's cost performance.