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This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

The authors investigate the impact of the stringency of environmental policy on the financial performance of European automobile manufacturers. This paper contributes to the debate about the impact of environmental policy on a firm's competitive performance.

The authors use cross-country sector-level panel data for 71 firms from 18 European countries from 2010 to 2019. The authors apply a fixed-effect model and then, to address the endogeneity issues, the authors use the generalized method of moments (GMM) model. To further examine the validity of the results, the authors use a data-mining modeling approach as a robustness test.

By considering the dynamic impact of environmental policy and overcoming the endogeneity issues, the results show that the impact of the stringency of environmental policy on a firm's financial performance depends on the time horizon: the stringency of environmental policy has a short-term negative impact but a long-term positive impact on a firm's financial performance.

The authors limited the study to the auto industry in Europe. In addition, future research could consider the impact of environmental policy on other financial performance indicators such as Return on Sales or Return on Equity. Also, it would be interesting to conduct a similar study in the United States or China using a firm-level data set to examine the robustness of the results.

Stringency of environmental policy improves a firm's financial performance in the long term. It is essential for firms and managers to consider the dynamic impacts of environmental policy on their financial performance and adopt a long-term perspective when evaluating the costs and benefits of complying with environmental regulations. The findings help management develop a long-term vision for investment and budget allocation. The results support management's view for strategic decision-making against the common budget argument and challenges for stockholders when it comes to adopting new technologies and planning long-term investment.

It is crucial for firms to recognize the broader societal benefits that come with environmental policy. Firms must not only focus on their financial performance but also on their social responsibility to protect the environment and contribute to the greater good. Therefore, firms must take a long-term perspective and recognize the broader societal benefits of environmental policy in order to make informed decisions that support both their financial success and their social responsibility.

This paper contributes to the literature by helping to explain the inconsistent results of studies about the impact of environmental policy on a firm's competitiveness. Using a firm's financial performance as one of the main metrics for competitiveness, this study takes into account both endogeneity and contemporaneity in evaluating the impact of the stringency of environmental policy on a firm's financial performance.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

The purpose of this paper is to investigate the relationship between CEOs' inside debt holdings (pension benefits and deferred compensation) and the operating leverage of the firms they manage, with the aim to examine whether CEO incentives play a role in corporate risk-taking.

The authors investigate the relation between CEO inside debt holdings (CIDH) (pension benefits and deferred compensation) and the operating leverage (DOL) of the firms they manage. Using a sample of 11,145 US firm-year observations over the period 2006–2017, the authors find a strong negative association between CIDH and DOL. Additional analyses reveal that the relationship between CIDH and DOL is more pronounced in firms with heightened agency issues, powerful CEOs and for CEOs with stronger professional networks. The results are robust to various sensitivity and endogeneity tests.

The authors find strong evidence confirming the expected negative association between CEO inside debt and DOL suggesting that firms with higher inside debt tend to maintain lower levels of operating leverage. These findings continue to hold with the alternative measure for the inside debt and operating leverage, and across a range of tests designed to rule out the possibility that the primary findings are in any way driven by potential endogeneity. In addition, the findings demonstrate that the presence of manager-shareholder agency conflicts can strengthen the inside debt–DOL relationship suggesting the strong role of inside debt in reducing firm risk.

Findings in this paper have implications for design of compensation structures so that corporate boards can establish incentives as a tool for risk management. A limitation of this study is that it is focused on one market, i.e. US listed companies, so the findings may not be applicable on a global scale.

To the best of the authors’ knowledge, this is the first study that links firm-level management of operating leverage through design of CEO inside debt incentives (two obvious choices for risk-reduction at the CEOs’ disposal include reducing financial risk through reduction of firm leverage and reducing operating risk through reduction of operating leverage). While use of firm leverage as an instrument of choice has been explored in the past, use of operating leverage to achieve risk reduction when CEO possess high inside holding, has received very little attention.

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.

This study aims to develop a conceptual framework for the role of chief financial officer (CFO) in an ever-changing environment. As previous research focused on responding to specific crises, there have been theoretical and practical gaps in the role of CFO. The study's goal is to fill a critical gap by developing a comprehensive and integrated set of roles to assist the CFO in a constantly changing environment.

Using a grounded theory approach, semi-structured interviews and observations were conducted with 21 CFOs from various industries in Thailand, including foreign multinational corporations and domestic companies with international operations. CFOs were asked how they frame their roles in the face of an ever-changing environment and how they prepare for the future.

The iCFO model is developed, which identifies the critical “core” roles of the CFO in securing the business foundation, as well as the “future opportunities” roles that function as growth engines for long-term business strength. The research delves into the importance of integrity, ethical mindset and corporate governance in the role of the CFO. The iCFO model is designed to help guide future research and provide practical applications for CFOs in both domestic and international contexts. The term “core” refers to the CFO’s primary responsibilities, which include driving profitability, managing risks and optimizing business performance. The “future opportunities” component focuses on the roles that CFOs can play in strengthening the future of business by optimizing investment efficiency, driving digital transformation and being the CEO’s business partner. The findings also emphasized “integrity,” which must encompass all decisions, actions or recommendations made by the CFO.

The study offers unique perspectives on an emerging economy, providing new insights. Through interviews with 21 CFOs, it contributes empirical evidence on the development of roles in accounting and finance, emphasizing good governance practices. The findings highlight the integrated role of the CFO and their self-reflection on their value within the company. Significantly, the study's implications are relevant and applicable to a global audience, particularly in developing economies that prioritize growth. Future studies could incorporate integrated thinking into the iCFO model to address social, environmental and economic factors, making it more universally relevant. Additionally, exploring the adoption of the chief value officer context in developing markets could enable CFOs to expand their focus beyond financial metrics, embracing a comprehensive approach to value creation. By integrating these concepts into the iCFO model, CFOs can effectively drive sustainable and impactful business outcomes on a global scale.

This study aims to investigate the association between corporate tax avoidance and environmental costs and disclosure in Indonesia and Australia for the research period 2015–2019. This study also analyzes corporate strategies for overcoming public concerns about tax avoidance activities, namely, the trade-off legitimacy and risk reduction strategies, through two mechanisms: the mediation and moderation roles of environmental disclosure on the relationship between environmental costs and tax avoidance activities.

The data consists of 675 and 235 observations for Australia and Indonesia, respectively, which were analyzed quantitatively using panel regression.

The results showed that the trade-off legitimacy or risk reduction strategies are not found to be implemented by companies in Indonesia, while in Australia, corporations use the trade-off legitimacy strategy to reduce risk and overcome the negative impact of tax avoidance activities. The results also provide empirical evidence on the impact of environmental costs on environmental disclosure in both countries.

This study contributes to the literature by providing the latest evidence on the role of environmental costs on environmental disclosure, which has rarely been investigated in previous studies.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

This study aims to examine the impact of some real variables such as real effective exchange rates, real mortgage rates, real money supply, real construction cost index and housing sales on the real housing prices.

This study uses a nonlinear autoregressive distributed lag (NARDL) model in the monthly period of 2010:1–2021:10.

The real effective exchange rate has a positive and symmetric effect. The decreasing effect of negative changes in real money supply on real housing prices is higher than the increasing effect of positive changes. Only positive changes in the real construction cost index have an increasing and statistically significant effect on real house prices, while only negative changes in housing sales have a small negative sign and a small increasing effect on housing prices. The fact that the positive and negative changes in real mortgage rates are negative and positive, respectively, indicates that both have a reducing effect on real housing prices.

This study suggests the first NARDL model that investigates the asymmetric effects on real housing prices instead of nominal housing prices for Turkey. In addition, the study is the first, to the best of the authors’ knowledge, to examine the effects of the five real variables on real housing prices.

A prime objective of the Swachh Bharat Abhiyan (SBA; Clean India Mission) is to motivate people to segregate their household waste. The purpose of this study is to assess the ground reality of waste management behaviour of Delhi residents with the help of a modified Value–Belief–Norm (VBN) model. Past researches point the need to include cost as a variable in the VBN model. This study fulfils this need and tests cost as one of the variables on the gathered data.

The research data were gathered by interacting with the people and the civic staff in the jurisdiction of the three Delhi municipalities through a stratified sampling technique (N = 250). The structural equation modelling was used to analyse the collected data.

The modified VBN model explains the waste management behaviour, but the variables do not follow the exact causal chain. Values, awareness of consequences, ascription of responsibility and personal norms all explain the resident's waste management behaviour. However, cost limits the resident's waste management behaviour.

The study could only achieve a moderate model fit; its sample size was small; and data were collected through self-reported questionnaire.

Three main practical implications of the study are: (1) While designing waste management solutions, due importance must be given to the cost to be borne by people for adopting these solutions. (2) Design such interventions that target residents' values to convince them to make the desired behavioural change. (3) People need be educated about the ways to sort waste and made aware of the importance of waste segregation in eradicating the urban waste mess.

The paper is an original contribution to testing a modified VBN model in predicting waste management behaviour. The modified model includes cost as a variable missing in the previous research. This research is useful in the backdrop of the SBA and provides suggestions for policymakers and pro-environment researchers.