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This paper investigates the effect of economic policy uncertainty on value of cash before and after the global financial crisis.

We investigate the relationship between economic policy uncertainty and value of excess cash based on the valuation model of Fama and French (1998). Baker et al. (2016) news-based index (BBD index) is employed to calculate measures of economic policy uncertainty. Our research sample includes 103,474 observations from 11,000 firms across 19 countries over the period 2004–2016.

We find that economic policy uncertainty is negatively “positively” related to value of cash in the pre-crisis “post-crisis” period. Moreover, we also document that the positive effect of economic policy uncertainty in the post-crisis period is stronger in financially constrained firms.

While prior studies find a relationship between economic policy uncertainty and cash levels or the effect of firm-level uncertainty on value of cash, this paper shows how economic policy uncertainty as an institutional environment factor affects value of cash. Moreover, it documents that economic policy uncertainty has opposite effects on value of cash before and after the global financial crisis.

本研究旨在探討經濟政策不確定性在全球金融危機之前及之後對現金價值的影響。

我們基於法馬及佛倫奇(1998) (Fama and French (1998)) 的估值模型，來探討經濟政策不確定性與過剩現金價值的關係。我們採用了貝克等人(2016) (Baker et al. (2016)) 以新聞訊息為基礎的指數 (BBD指數) 、來計算經濟政策不確定性的程度。我們的研究樣本包括橫跨19個國家、涵蓋期為2004年至2016年、取自11,000間公司之103,474個觀察。

我們發現經濟政策不確定性與現金價值在危機前時期成負相關,在危機後時期則成正相關。而且,我們也記錄了在危機後時期經濟政策不確定性的正面影響於財務受限的公司會較大的情況。

過去的研究發現了經濟政策不確定性與現金水平之間存有關係、及企業層面的不確定性對現金價值的影響。唯本研究顯示了經濟政策不確定性作為一機構環境因素,如何影響現金價值；同時，亦記錄了經濟政策不確定性在全球金融危機之前及之後對現金價值會有相反影響的情況。

The purpose of this paper is to compare the value outcomes of the cost approach to the DCF profits method when valuing specialised property under different scenarios as a test for choice of method or model uncertainty; and to quantify valuation uncertainty under each scenario and to argue for an increasing adoption of the profits method of valuation.

A qualitative case study approach was used to analyse four physical valuations performed in practice under four specific scenarios, namely, a business-as-usual scenario, an underperforming business scenario, an expanding capacity scenario and a combined business-as-usual funding a start-up joint venture scenario.

The cost approach relative to the DCF profits approach consistently under-values specialised property under business-as-usual and business expanding scenarios while it over-values in instances of underperforming business scenario.

Financial institutions that predominantly uses or accepts the cost approach for valuing specialised property should consider adopting the DCF profits approach as the default approach when valuing for mortgage lending purposes. Business owners of specialised properties should contract practitioners knowledgeable and skilled in the application of the DCF profits method.

This paper quantifies choice of method or model uncertainty of four different scenarios of specialised properties where both the cost approach and DCF profits methods of valuation were employed. It suggests the adoption of the DCF profits method as the default method of valuation for specialised property.

The purpose of this paper is to investigate firm behaviors on patent examination request under the deferred patent examination system in Korea. The authors examine firm decisions on whether and when to request patent examinations when they face both uncertainty about invention’s value and market competition.

The authors provide a simple theoretical model and test a couple of hypothesis using Korea patent data. The authors employ KIPO (Korean intellectual patent office) patent applications data during 2006–2009 and incorporate it with firm financial data retrieved from1 Korea investor service-financial analysis system (KIS-FAS) database in Korea. The authors use the variation in the probability of lapsed patent applications filed in the same year and in the same technology field (at the four-digit IPC class level) of a patent application i as a proxy for the value of uncertainty, and further use one minus a firm’s market share (at the three-digit SIC industry level) as an indicator of the market competition faced by the firm/applicant.

The authors find that the examination requests of firms in Korea have interesting bipolar distribution, and both uncertainty about an invention’s value and market competition have significant impacts on firm’s decision for examination request. Applicants tend to utilize option value of waiting when uncertainty is high, but market competition attenuates the option value: the higher the competition, the less likely applicants are to delay or forego examination.

The authors’ study makes interesting contributions to the literature on the optimal design of the patent system in general and the deferred patent examination request system in particular. By considering the roles of both uncertainty and market competition in firm decisions, it provides a more comprehensive perspective on the deferred patent examination system. The study also provides empirical evidences on the broader research topic regarding firm decision for irreversible investment when faced with both uncertainty and competition, for which a strand of theoretical literature exists but empirical literature is largely limited. This study, which explicitly takes into account uncertainty and market competition, extends this line of empirical literature and fills the gap in the literature.

The purpose of this paper is to develop and test a model of the uncertainties and benefits influencing the repurchase intentions of buyers in cross-border e-commerce (CBEC).

The authors draw on the valence framework to hypothesize effects of positive valences (utilitarian benefits) along with negative valences (pre- and post-contractual uncertainties) on buyers’ repeat purchase intentions. Data were collected using an online survey from 378 international B2C buyers on a CBEC platform in China.

Results explain 51.4 percent of the variance and reveal that overall value, as determined by monetary saving, convenience and product offerings as positive valences, exerts the strongest effect on repeat purchase intention. However, negative valences remain significant, and are particularly salient for female shoppers.

The authors extend the valence theory into the study of repeat purchase behavior and contribute to much needed literature on why consumers return to repurchase from a CBEC platform.

Repeat purchase and loyalty of online consumers is essential for success of e-commerce providers. The results help online providers competing in international markets understand how buyers form repurchase intentions based on their evaluations of both value and uncertainty.

Buyer behavior in CBEC has received relatively less attention than domestic e-commerce. This paper is among the first to examine how both positive and negative valences combine to effect repurchase intention of international buyers in CBEC.

Past research has shown that culture has significant effects on people's evaluation of and responses to risk. Despite this important role, the supply chain risk literature has been silent on this matter. The purpose of this paper is to examine the impact of cultural value orientations on managerial perception of and responses to a supply disruption risk.

The authors conduct a scenario-based experiment to investigate the effect of cultural value orientations – i.e. individualism-collectivism and uncertainty avoidance – on individuals' perception of risk and supplier switching intention in the face of a supply disruption.

The findings highlight the negative effect of individualism-collectivism on disruption risk perception and switching intention in high uncertain circumstances. However, these relationships are non-significant in relatively less uncertain situations. Moreover, the findings show that the impact of uncertainty avoidance on risk perception and supplier switching is positive and significant in both low and high uncertain circumstances.

Extant research has traditionally assumed that when confronted with disruption risks, managers make decisions using an economic utility model, to best serve the long-term objectives of the firm. This paper draws from advances of behavioural research to show that cultural value orientations influence such decisions through a mediating mechanism of subjective risk perception.

We discuss recent developments in real options theory and its applications to strategic management research, examine the potential difficulties in implementing real options in theory and practice, and propose several areas for future research. Our review shows that real options theory has provided substantial insights into investment and exit decisions as well as into the choice of investment modes. In addition, extant research studies have contributed significantly to our understanding of whether and how organizations can benefit from real options. Future research that addresses difficulties in applications will further advance both real options theory and practice in strategic management. We call for future generations of research to enhance the impact of real options as an emerging dominant conceptual lens in strategic management.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.

In this paper, we show that reducing supply chain uncertainty increases responsiveness and thereby benefits bottom line performance as assessed via total cycle time reduction. We term this effect as the uncertainty reduction principle. To enable uncertainty reduction we use the uncertainty circle to focus on the sources to be eliminated. We also show that these sources of uncertainty can react and magnify in a flywheel effect caused by poor supply chain management. A supply chain audit methodology is described for identifying and codifying uncertainty. The proposition advanced herein is that smooth material flow leads to and statistically correlates with uncertainty reduction. Examples are given of good real‐world supply chain practices thus identified and subsequently improved. Transferability of the uncertainty reduction principle is assured by establishing readily assimilated “best practice” guidelines via the study of “exemplar” operating characteristics.

Uncertainty in data, whether in real-valued or integer-valued data, may result in infeasible optimal solutions or unreliable efficiency scores and ranking of decision-making units. To handle the uncertainty in integer-valued factors in data envelopment analysis (DEA) models, this study aims to propose a robust DEA model which is applicable in the presence of such factors.

This research focuses on the application of fuzzy interpretation of efficiency to a mixed-integer DEA (MIDEA) model. The robust optimization approach is used to address the uncertain integer-valued parameters in the proposed MIDEA model.

In this study, the authors proposed an MIDEA model without any equality constraint to avoid the arise problem by such constraints in the construction of the robust counterpart of the conventional MIDEA models. We have studied the characteristics and conditions for constructing the uncertainty set with uncertain integer-valued parameters and a robust MIDEA model is proposed under a combined box-polyhedral uncertainty set. The applicability of the developed models is shown in a case study of Malaysian public universities.

This study develops an MIDEA model equivalent to the conventional MIDEA model excluding any equality constraint which is crucial in robust approach to avoid restricted feasible region or infeasible solutions. This study proposes a robust DEA approach which is applicable in cases with uncertain integer-valued parameters, unlike previous studies in robust DEA field where uncertain parameters are generally assumed to be only real-valued.

The purpose of this paper is to explain why the high quality cassava flour (HQCF) value chain in Nigeria has not performed as well as expected. The specific objectives are to: analyse important sources of uncertainty influencing HQCF value chains; explore stakeholders’ strategies to respond to uncertainty; and highlight the implications of different adaptation strategies for equity and the environment in the development of the value chain.

The authors used a conceptual framework based on complex adaptive systems to analyse the slow development of the value chain for HQCF in Nigeria, with a specific focus on how key stakeholders have adapted to uncertainty. The paper is based on information from secondary sources and grey literature. In particular, the authors have drawn heavily on project documents of the Cassava: Adding Value for Africa project (2008 to present), which is funded by the Bill & Melinda Gates Foundation, and on the authors’ experience with this project.

Policy changes; demand and supply of HQCF; availability and price of cassava roots; supply and cost of energy are major sources of uncertainty in the chain. Researchers and government have shaped the chain through technology development and policy initiatives. Farmers adapted by selling cassava to rival chains, while processors adapted by switching to rival cassava products, reducing energy costs and vertical integration. However, with uncertainties in HQCF supply, the milling industry has reserved the right to play. Vertical integration offers millers a potential solution to uncertainty in HQCF supply, but raises questions about social and environmental outcomes in the chain.

The use of the framework of complex adaptive systems helped to explain the development of the HQCF value chain in Nigeria. The authors identified sources of uncertainty that have been pivotal in restricting value chain development, including changes in policy environment, the demand for and supply of HQCF, the availability and price of cassava roots, and the availability and cost of energy for flour processing. Value chain actors have responded to these uncertainties in different ways. Analysing these responses in terms of adaptation provides useful insights into why the value chain for HQCF in Nigeria has been so slow to develop.

Recent developments suggest that the most effective strategy for the milling industry to reduce uncertainty in the HQCF value chain is through vertical integration, producing their own cassava roots and flour. This raises concerns about equity. Until now, it has been assumed that the development of the value chain for HQCF can combine both growth and equity objectives. The validity of this assumption now seems to be open to question. The extent to which these developments of HQCF value chains can combine economic growth, equity and environmental objectives, as set out in the sustainable development goals, is an open question.

The originality lies in the analysis of the development of HQCF value chains in Nigeria through the lens of complex adaptive systems, with a particular focus on uncertainty and adaptation. In order to explore adaptation, the authors employ Courtney et al.’s (1997) conceptualization of business strategy under conditions of uncertainty. They argue that organisations can assume three strategic postures in response to uncertainty and three types of actions to implement that strategy. This combination of frameworks provides a fresh means of understanding the importance of uncertainty and different actors’ strategies in the development of value chains in a developing country context.