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The purpose of this paper is to investigate whether financial analyst coverage affects the dissemination of disclosed operating lease information into cash flow predictions and stock prices.

The difference in lease expense between capital/finance lease and operating lease reporting is estimated based on the approach in Hsieh and Su (2015). This difference is referred to as the earnings impact from operating lease capitalization and is only available from footnotes. The authors then include the level of financial analyst following in a cash flow model to study its impact on the cash flow predictive value of the earnings impact. Similarly, the level of financial analyst following is inserted in an earnings-return model to assess the effect of analyst coverage on the association between contemporaneous stock returns and earnings impact.

The authors find that the cash flow predictive value of the earnings impact shifts to the interaction between analyst coverage and the earnings impact, suggesting that the decision-usefulness of the earnings impact is conditioned on the level of analyst following. Nevertheless, the authors find that the earnings impact continues to have explanatory value for the contemporaneous stock returns, while the interaction between analyst coverage and the earnings impact does not. This finding suggests that the earnings impact is already fully reflected in stock prices regardless of analyst following.

Since the estimation of the earnings impact from reporting operating leases as capital leases is based on the method developed by Imhoff et al. (1991), the results and inferences are thus constrained by the validity of the method.

The authors find that financial analyst activities accelerate the incorporation of the earnings impact from operating lease capitalization in cash flow predictions, but it does not promote the impounding of the earnings impact into stock prices. This finding suggests that financial analysts' influence on the dissemination of the earnings impact hinges on the type of economic activity, and failing to consider the financial analyst following in studying the cash flow predictive value of the earnings impact would obscure the findings.

The authors extend the findings of prior research that financial analysts' activities promote the incorporation of firm-specific information into stock prices by investigating the impact of financial analysts on the dissemination of disclosed operating lease information.

This paper aims to examine the impact on firm financial distress by industry of one of the most recent accounting changes in the treatment of operating leases, Financial Accounting Standard Board (FASB) Accounting Standards Update (ASU) No. 2016–02, Leases released February 25, 2016. ASU 2016–02, also known as ASC 842, considerably changed how firms account for operating leases.

The authors use the Black–Scholes–Merton (BSM) option pricing methodology to estimate the change in default likelihood (DL) of nine different industries surrounding the adoption of ASC 842. In addition, the authors use univariate and multivariate analysis to test the statistical significance of firm-related factors.

The authors provide evidence that numerous industry’s DL increased following the FASB’s announcement of the new standard (ASC 842) regarding increased transparency in lease recognition. The effect is especially significant within the energy industry, although it is also shown in the consumer durables, manufacturing, hi-tech equipment, telecom, retail and wholesale and transportation industries. In addition, the authors find the effect is more pronounced for firms with high leverage, low financial slack, low operating return on assets, small market value and accounting for non-balance sheet recorded leases.

By investigating different industries, this study’s findings provide crucial insight to managers seeking lease financing as an operational strategy in a post-implementation environment and help them understand the impact of this new standard on their firm. Furthermore, this study answers the call of policy makers and academics to provide insight into the impact of updated leasing standards.

This is the only empirical study that examines the impact of ASC 842 on the DL of publicly traded firms by industry.

The International Accounting Standards Board (IASB) and Financial Accounting Standards Board (FASB) have given relief to lessees in response to the coronavirus (COVID-19) pandemic. However, it is not clear why any relief from the requirements in International Financial Reporting Standards (IFRS) or the Accounting Standards Codification (ASC) should be necessary. The purpose of this paper is to highlight weaknesses in how the IASB and FASB developed their leases Standards, and why those Standards are not robust enough to cope with a shock to the economic system.

The COVID-19 relief suspends some features of the leasing requirements rather than changing them. What if other economic or regulatory events cause the same circumstances to arise?

Have COVID-19 exposed weaknesses in the leasing standards that should have been avoided when they were developed or is COVID-19 the problem?

Analysis of actual board discussions and staff papers is unusual and provides insights into the standard-setting process.

The purpose of this paper is to examine the influence of manager ability on a firm’s choice of lease classification and the decision to capitalize vs lease firm-specific assets.

The authors use regression analysis to examine the association between manager ability, lease classification and asset specificity.

Using 31,110 firm-year observations from 1998 to 2013, the authors find a significant positive relationship between manager ability and the decision to classify leases as operating. The authors also find that high-ability managers are more likely to capitalize, rather than lease, specialized firm-specific assets.

The results imply that manager ability influences the choice of lease classification, which provides some support for the recent changes to lease accounting in Accounting Standard Update (ASU) 2016-02. The authors also show that asset specificity may serve as a mitigating factor in high-ability managers’ preference for operating leases, which implies that high-ability managers’ concerns with operational efficiency outweigh the benefits of off-balance sheet financing in their purchasing decisions if the asset in question is firm-specific.

The findings may be useful to boards of directors, investors and accounting academics concerned with the role that managerial ability plays in operational decision making and financial reporting.

The results imply that high-ability managers prefer off-balance sheet financing, which is unlikely to limit their access to external capital, but that this relationship is mitigated if the firm requires highly specialized assets.

Drawing on the dynamic capabilities theory, this paper proposes that supply chain (SC) strategies (i.e. the lean SC and agile SC strategies) will mediate the relationship between big data analytics (BDA) and SC performance. Furthermore, from the perspective of strategic alignment, this study hypothesizes that the effect of the SC strategy on SC performance is differently moderated by the information system (IS) strategy (i.e. the IS innovator and IS conservative strategies).

This study used 159 match-paired questionnaires collected from Chinese firms to empirically test the hypotheses.

Results show the positive direct and indirect impact of BDA on SC performance. Specifically, the lean and agile SC strategies mediate the relationship between BDA and SC performance. Furthermore, the results indicate that the IS innovator and IS conservative strategies differentially moderate the effect of the lean and agile SC strategies on SC performance. Specifically, the IS innovator strategy positively moderates the effect of the agile SC strategy on SC performance. By contrast, the IS conservative strategy positively moderates the effect of the lean SC strategy on SC performance but negatively moderates the effect of the agile SC strategy on SC performance.

This study provides a comprehensive understanding of how SC and IS strategies can help firms leverage BDA to improve SC performance.

This study aims to examine the effects of strategic sourcing (SS) on lean supply chain (LSC) and agile supply chain (ASC) strategies and investigate the role of these concepts on development of competitive performance.

A proposed research model and hypotheses are tested by using cross-sectional e-mail survey data collected from the manufacturing firms operating in Turkey. SS is conceptualized as a second-order factor. Structural equation modeling is used to test the proposed hypotheses.

This study reached the conclusion that SS affects LSC and ASC strategies positively. Additionally, it is seen that these concepts are effective in improvement of competitive performance.

The results are important in terms of emphasizing the significance of SS in improvement of the lean and agile nature of the supply chain.

This study contributes to the literature by providing empirical evidence regarding the relationships among SS, supply chain strategies and competitive performance.

This study was carried out on the plant level where one person from each organization responded to the survey.

This paper empirically examines whether the order of liability and preferred stock accounts presented on the balance sheet is consistent with how the stock market values their riskiness.

This paper measures a firm’s riskiness with idiosyncratic risk and employs the first-difference design to test the relation between idiosyncratic risk and the order of current liabilities, noncurrent liabilities and preferred stock, respectively. Further, the paper tests whether operating liabilities are viewed as riskier than financial liabilities. Finally, the authors partition their sample based on the degree of financial distress and investigate whether the results differ between the two subsamples.

The paper finds that current liabilities are viewed as riskier than noncurrent liabilities and preferred stock is viewed as less risky than current and noncurrent liabilities, consistent with the ordering on the balance sheet. Further, the paper finds that operating liabilities are viewed as riskier than financial liabilities. Finally, the authors find that total liabilities and preferred stock (redeemable and convertible classes) are viewed as riskier for distressed firms than for nondistressed firms.

The authors thoroughly investigate the riskiness of several classes of claims and document that the classification of liabilities and preferred stock classes is relevant to common stockholders for assessing their associated risk.

Theorising from a resource-based view perspective, the intersection of supply chain management and the use of information technology (IT) has been investigated in this study. This paper aims to investigate supply chain performance (SCP) as an essential outcome of the use of IT and explores the effect of supply chain collaboration (SCC) on SCP. In addition, volume uncertainty (VU) has been explored and tested to establish whether various associated uncertainties can be mitigated when the use of IT is involved.

A sample of 121 senior executives from agri-tech firms was collected by travelling and meeting the executives in person in various states of India. Structural equation modelling was used to test the hypothesized relationship of VU to SCP via the use of IT and SCC.

The results show that VU significantly impacts SCC via the use of IT and SCP via SCC. The use of IT positively and significantly impacts SCP via SCC.

Witnessing the potential benefits of the emerging use of IT in the uncertainty reduction as reported in this study, agri-tech firms operating in emerging rural and agricultural economies can enhance SCC to improve SCP.

This study unfolds how risks in agricultural supply chains (ASCs) sourced because the VU can be mitigated through the use of IT and SCC to influence SCP in rural agricultural and developing economies.

VU at agri-tech firms and farmers is a ground reality that has led to an inability to plan and prepare, resulting in wastages and disruptions in ASCs and farmers’ struggles.

In the context of emerging economies, the purpose of this paper is to seek the critical success factors (CSFs) of supply chain and identify their relationships to enhance the supply chain performance (SCP) in a sample of Indian manufacturing firms.

On the basis of a comprehensive literature review, the authors conducted this study and proposed a new model of antecedent and outcomes for SCP in emerging markets. The empirical data for this study were drawn from a survey of 227 Indian firms, resulting in a response rate of 52 percent. The method of confirmatory factor analysis was applied to refine the CSFs and SCP scale for empirical analysis. The data were analyzed by employing the structural equation modeling technique.

The results reveal that all the identified CSFs, namely, agility, flexibility, flexible innovation, information and communication technology, collaboration among conglomerate divisions, process structure, and training and leadership programs, are positively associated with SCP. The empirical study of 227 Indian firms lent good support to the hypotheses and validates it by the data analysis. Consequently, these findings highlight the prominence of these factors of supply chain for gaining a sustainable competitive advantage in emerging market scenario.

The study emphasizes on CSFs in emerging markets that will help to boost the organization’s SCP through agility and flexibility in supply chain. This study is applicable for growing markets in which there is ample amount of resources.

As economic growth stagnates in developed economies, emerging markets grow at near double-digit rates. Somehow, this study is pioneer in terms of enhance SCP in emerging market scenario. Moreover, the outcome of the study could provide empirical evidence of the effects of CSFs on SCPs.

This paper aims to present a closed-loop supply chain (CLSC) optimization problem for a perishable agricultural product to achieve three pillars of sustainability, including minimizing total network costs and carbon dioxide emissions from different network activities and maximizing responsiveness to demands simultaneously.

The research problem is formulated as a multi-objective mixed-integer linear programming model, and classical approaches, including the LP-Metric and weighted Tchebycheff method, have been applied to solve the optimization model. A set of test problems has been proposed to validate the model, and the results are presented.

Computational time to find Pareto optimal solutions by using the weighted Tchebycheff method was twice as much as that of the LP-Metric method. Also, the result of the study is a mathematical model that can be applied to other products that are close to the fruit, such as vegetables.

The present study is limited to fruits supply chains and the inventory is considered at the distribution centers only. The study also considers only one type of transport.

The paper can assist supply chain managers to define strategies to achieve a sustainable CLSC network configuration for the fruits.

This study is one of the early studies to consider environmental indicators in fruits supply chain design along with two other indicators of sustainability, namely, economic and social indicators. Therefore, this can help supply chain managers to achieve sustainability by optimizing location decisions, inventory quantities and flow between facilities.