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The relevance of finance for strategy is probably never greater than during a recession. We argue that the strategy literature has been virtually silent on the issue of recessions, and that this constitutes a regrettable sin of omission. Recessions are also periods when the commonly held view of financial markets in the strategy literature – efficient, and therefore strategically irrelevant – is particularly misplaced. A key route to rectify this omission is to focus on how recessions affect investment behavior, and thereby firms’ stocks of assets and capabilities which ultimately will affect competitive outcomes. In the present chapter, we aim to contribute by analyzing how two key aspects of recessions, demand reductions and reductions in credit availability, affect three different types of investments: physical capital, R&D and innovation, and human- and organizational capital. We synthesize and conceptualize insights from finance- and macroeconomics about how recessions affect different types of investments and find that recessions not only affect the level of investment, but also the composition of investments. Some of these effects are quite counterintuitive. For example, investments in R&D are both more and less sensitive to credit constraints than physical capital is, depending on available internal finance. Investments in human capital grow as demand falls, and both R&D and human capital investments show important nonlinearities with respect to changes in demand.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

The purpose of this paper is to investigate the relationship between working capital management and corporate performance with financial constraints.

This study uses large panel sample of Chinese listed firms over the period 2005–2015 using system generalized method of moments (GMM) estimator that controls unobserved heterogeneity of individual firms well and GMM methodology is robust to address endogeneity issues.

Empirical evidence finds inverted U-shaped relationship between working capital and corporate performance and exhibits similar evidence for financially constrained firms. Evidence shows impact of high sales and discounts on early payments at low level of working capital and dominance of opportunity cost and cost of external finance at high level of working capital. The findings of the results show that optimal working capital level of financially constrained firms is relatively lower due to high cost of external capital and debt rationing. The results also indicate that on average NET is significantly lower for firms with Tobin’s Q>1 than firms with Tobin’s Q=1, and suggest that aggressive working capital management is significantly and positively associated with higher corporate values.

This paper is among few that complement the existing literature by providing evidence that inverted U-shaped relationship between working capital management and corporate performance also exists in the context of Chinese listed non-financial firms. Exclusively, the relationship of working capital and corporate performance with linkage of financial constraints is scant in the context of Chinese listed non-financial firms.

The purpose of this paper is to extend the literature on trade receivables and trade payables by examining the determinants of net trade credit.

To do that, a sample of 67,047 firms in the UK with 443,190 firm year observations is used.

The results are robust to unobserved heterogeneity and industry effects. The evidence suggests that firms with more inventories, market share and are financially distressed invest less in trade credit. Moreover, higher operating cash flow, annual sales growth, export propensity, access to bank credit and larger firms lead to higher investment in trade credit.

Additionally, the paper broadens the scope of the literature by analysing the determinants of net trade credit around the financial crisis and industry competitiveness.

Existing studies that documented the effect of financial distress on trade credit provisions did not include measures financial constraint. It is possible that financial distress is tie to financial constraints, and both financial distress and financial constraints mutually reinforce each other in their effects on trade credit provision. The purpose of this study is to evaluate the effects of financial constraint and financial distress on trade credit provisions in the UK FTSE 350 listed firms.

This study employs panel data in the estimation of the determinants of accounts payables and accounts receivables of the UK FTSE 350 firms from 2009 to 2017.

This study finds that financial distress has significant positive effect on accounts payables and a significant negative effect on accounts receivables. Financial constraints have significant negative effect on accounts payables and a significant positive effect on accounts receivables.

Trade creditor desiring to maintain an enduring product-market relationship grant more concessions to customer in financial distress. The amount of trade credit that sellers provide to financially constrained firm is an increasing function of the buyer's creditworthiness. The urgent cash needs of financially distressed firms lead them to sell trade receivables to factoring company leading to reduction in trade receivables. Firm facing external financing constraints increase trade credit to customers in anticipation of cash flow inflow to enhance liquidity.

This study shows that financial distress and financial constraints mutually reinforce each other in their effects on trade credit provisions, and firm's financing condition contributes to divergence in trade credit policies.

Purpose: In reality, financial decisions are made under conditions of asymmetric information that results in either favorable or adverse selection. As far as financial decisions affect growth of the firm, the latter must also be affected by either favorable or adverse selection. Therefore, the core objective of this chapter is to examine the determinants of each financial decision and the effects on growth of the firm under conditions of information asymmetry.

Design/Methodology/Approach: This chapter uses data for the non-financial firms listed in S&P 500. The data cover quarterly periods from 1989 to 2014. The statistical tests include linearity, fixed, and random effects and normality. The generalized method of moments estimation method is employed in order to examine the relative significance and contribution of each financial decision on growth of the firm, respectively. Standard and proposed proxies of information asymmetry are discussed.

Findings: The results conclude that there is a variation in the impact of financial variables on growth of the firm at high and low levels of information asymmetry especially regarding investment and financing decisions. A similar picture emerges in the cases of firm size and industry effects. In addition, corporate dividen d policy has a similar effect on firm growth across all asymmetric levels. These findings prove that information asymmetry plays a vital role in the relationship between corporate financial decisions and growth of the firm. Finally, the results contribute to the vast literature on the estimation of information asymmetry by demonstrating that the classical and standard proxies for information asymmetry are not consistent in terms of the ability to differentiate between favorable or adverse selection (which corresponds to low and high level of information asymmetry).

Originality/Value: This chapter contributes to the related literature in two ways. First, this chapter offers updated empirical evidence on the way that financing, investment, and dividends decisions are made under conditions of favorable and adverse selection. Other related studies deal with each decision separately. Second, the study offers new proxies for measuring information asymmetry in order to reach robust estimates of the effects of financial decisions on growth of the firm under conditions of agency problems.

The purpose of this paper is to provide new insights about investment-cash flow sensitivities (ICFS) as a representative of financial constraints, by examining panel data consisting of 288 listed firms in Pakistan.

This study uses a panel data methodology and first difference generalized method of moments to control the problems of heterogeneity and endogeneity. By five different criteria, estimations are made for full and pre-classified sub-samples. Sargan test and Arellano-Bond serial correlation statistic are used for identification and validation of instruments and model.

According to the results, the ICFS has increased monotonically with the level of financial constraints. Further, the results depict that ICFS for the constrained group is much higher as compared to the unconstrained group. Overall, the result illustrates positively significant ICFS.

This study confirms signs of imperfections in the capital market, which leads to financial markets inaccessibility preceded by high under-investment costs and low social and economic development. Thus, proper policy designing and instigation are necessary for the subsidies, taxation, and foreign direct investment and later for financial market development and promotion of private corporate investment.

Previous studies have mostly focused on developed countries where large listed companies work in well-developed financial markets and do not face severe financial constraints because of the greater market integration (Bekaert et al., 2011, 2013) and superior investor protection laws (Djankov et al., 2008; La porta et al., 1998). However, this study focuses on listed companies from the emerging Pakistani market, which will bring forth the interesting aspects of ICFS and will enhance the existing literature effectively.

Electric mobility as a service (eMaaS) is suggested as a possible solution to ease transportation and lessen environmental issues by providing a collaborative transport sharing infrastructure that is based on electric vehicles (EVs) such as electric cars, electric bicycles and so on. Accordingly, this study aims to propose a multi-tier architecture to support the collection, processing, analytics and usage of mobility data in providing eMaaS within smart cities. The architecture uses application programming interfaces to enable interoperability between different infrastructures required for eMaaS and allow multiple partners to exchange and share data for making decision regarding electric mobility services.

Design science methodology based on a case study by interview was used to collect data from an infrastructure company in Norway to verify the applicability of the proposed multi-tier architecture.

Findings suggest that the architecture offers an approach for collecting, aggregating, processing and provisioning of data originating from sources to improve electric mobility in smart cities. More importantly, findings from this study provide guidance for municipalities and policymakers in improving electric mobility services. Moreover, the author’s findings provide a practical data-driven mobility use case that can be used by transport companies in deploying eMaaS in smart cities.

Data was collected from a single company in Norway, hence, it is required to further verify the architecture with data collected from other companies.

eMaaS operates on heterogeneous data, which are generated from EVs and used by citizens and stakeholders such as city administration, municipality transport providers, charging station providers and so on. Therefore, the proposed architecture enables the sharing and usage of generated data as openly available data to be used in creating value-added services to improve citizen’s quality of life and viability of businesses.

This study proposes the deployment of electric mobility to address increased usage of vehicles, which contributes to pollution of the environment that has a serious effect on citizen’s quality of life.

This study proposes a multi-tier architecture that stores, processes, analyze and provides data and related services to improve electric mobility within smart cities. The multi-tier architecture aims to support and increase eMaaS operation of EVs toward improving transportation services for city transport operators and citizens for sustainable transport and mobility system.