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Uncertainty in the early development of digital business startups can benefit from data-driven testing of hypotheses. Startups face uncertainty not only in product development, but also over the structure of the business model and the nature of the customer or market to address. The authors conceptualize a new model, the Lean Discovery Process (LDP), which focuses on market-based testing from the early business idea through to fully realized product stages of an innovation. The purpose of this paper is to highlight a methodology to help digital business reduce uncertainty and apply lean principles as early as possible in the development of a business concept.

Examining literature in lean startups, lean user experience and lean software development, the authors highlight underlying assumptions of existing lean models. The authors then examine the LDP using the case of raiserve, a social entrepreneurship startup that focuses on the management of cause-based voluntary service.

Existing literature focuses on product development against an assumed customer base. Early hypothesis testing can be applied to business concept development to substantially reduce cost and time to market.

Further investigation of different forms of uncertainty in digital startups can open up opportunities to further apply lean methodologies. A more extensive empirical study to measure the potential impact is warranted.

The authors conceptualize the minimum viable customer and support early testing with concepts from market research and collective intelligence. The authors demonstrate early opportunities to apply lean principles and rigorous hypothesis testing in an LDP that results in significant reductions in time and expense of product development.

The purpose of this paper is to show that necessary condition hypotheses are important in operations management (OM), and to present a consistent methodology for building and testing them. Necessary condition hypotheses (“X is necessary for Y”) express conditions that must be present in order to have a desired outcome (e.g. “success”), and to prevent guaranteed failure. These hypotheses differ fundamentally from the common co‐variational hypotheses (“more X results in more Y”) and require another methodology for building and testing them.

The paper reviews OM literature for versions of necessary condition hypotheses and combines previous theoretical and methodological work into a comprehensive and consistent methodology for building and testing such hypotheses.

Necessary condition statements are common in OM, but current formulations are not precise, and methods used for building and testing them are not always adequate. The paper outlines the methodology of necessary condition analysis consisting of two stepwise methodological approaches, one for building and one for testing necessary conditions.

Because necessary condition statements are common in OM, using methodologies that can build and test such hypotheses contributes to the advancement of OM research and theory.

In order to cope with the challenge of developing successful fast moving consumer goods (FMCG) innovations, market research vendors offer several methodologies to test concepts. The purpose of this article is to examine the discrepancy between the well-established experimental real store methodology and the most recent of these alternative methodologies that is the virtual store.

A parallel testing of a new adult cereal was conducted in France with 200 shoppers in each store.

Results show that all attitudinal measurements are similar in terms of cognition and conation, but affect and behavior cannot be compared across both methodologies. In conclusion, virtual store testing is a new method that does not exactly fit with one of the previous.

The study is limited to a single product and should be generalized to more product categories.

Virtual store should be used carefully in order to take capital expenditure decisions. It generates different attitudes and behaviors, but more research is needed in order to debate on predictability.

With the emergence of virtual stores to test FMCG innovations, this paper is of high value for practitioners who have to proceed to several tests, with different objectives, before a product launch.

This paper aims to provide a methodology for designing and conducting solvency stress tests, under the standardised approach as per IFSB-15, including the establishment of macro-financial links, running scenarios with variation of assumptions and stress scenario parameters; apply and illustrate this methodology by providing a stylised numerical example through a tractable Excel-based framework, through which Islamic Commercial Banks (ICBs) can introduce additional regulatory requirements and show that they would remain in compliance with all capital requirements after a moderate to severe shock; and identify the potential remedial actions that can be envisaged by an ICB.

The paper uses the data of the one of the groups to which certain amendments and related assumptions are applied to develop a stylised numerical example for solvency stress-testing purposes. The example uses a Stress Testing Matrix (STeM; a step-by-step approach) to illustrate the stress-testing process. The methodology of the paper uses a two-stage process. The first stage consists of calculating the capital adequacy ratio (CAR) of the ICB using the IFSB formulae, depending on how the profit sharing investment account (PSIA) are treated in the respective jurisdiction. The second stage is the application of the stress scenarios and shocks.

Taking into account the specificities of ICBs such as their use of PSIA, the results highlighted the sensitivity of the CAR of an ICB with respect to the changes in the values of alpha and the proportion of unrestricted PSIA on the funding side. The simulation also indicated that an ICB operating above the minimum CAR could be vulnerable to shocks of various degrees of gravity, thus bringing the CAR below the minimum regulatory requirement and necessitating appropriate remedial actions.

The paper highlights various implications and relationships arising out of stress testing for ICBs, including the vulnerability of an ICB under defined scenarios, demanding appropriate immediate remedial actions on future capital resources and capital needs. The findings of the paper provide a preliminary discussion on developing a comprehensive toolkit for the ICBs similar to what is developed by the International Monetary Fund Financial Sector Assessment Programme.

This paper focuses on the gap with respect to the stress testing of capital adequacy. The main contribution of the paper is twofold. The first is the development of an STeM – a step-by-step approach, which provides a method for simulating solvency (i.e. capital adequacy) stress tests for ICBs; the second is the demonstration of the potentially crucial impact of profit-sharing investment accounts and the way they are managed by ICBs (notably the smoothing of profit payouts) in assessing the capital adequacy of the ICBs.

In all existing theoretical papers on causality it is assumed that the lag length is known a priori. However, in applied research the lag length has to be selected before testing for causality. The purpose of this paper is to suggest that in investigating the effectiveness of various Granger causality testing methodologies, including those using bootstrapping, the lag length choice should be endogenized, by which we mean the data‐driven preselection of lag length should be taken into account.

The size and power of a bootstrap test with endogenized lag‐length choice are investigated by simulation methods. A statistical software component is produced to implement the test, which is available online.

The simulation results show that this test performs well. An application of the test provides empirical support for the hypothesis that the UAE financial market is integrated with the US market.

The empirical results based on this test are expected to be more precise.

This paper considers a bootstrap test for causality with endogenous lag order. This test has superior properties compared to existing causality tests in terms of size, with similar if not better power and it is robust to ARCH effects that usually characterize financial data. Practitioners interested in causal inference based on time series data might find the test valuable.

The supervisory stress test evaluates the capital adequacy and profit-generation capacity of systemic banking institutions under baseline and adverse macroeconomic scenarios. This study aims to assess the financial and informational role of European stress tests and substantiate the impact of their disclosures by examining the EU-wide 2018 stress test vis-à-vis the EU-wide 2021 stress test in terms of how and to what extent the stock prices of the stress-tested banks have been affected.

This study applies standard event study methodologies to evaluate the reactions of market participants during the EU-wide 2018 and 2021 stress test exercises. We examine several “large” events in both the exercises for a selected sample of European banks.

The results of our event study analysis show that the EU-wide 2018 and 2021 stress tests come subsequent to considerable abnormal price movements. The announcement of stress test results triggered tangible investor reactions, indicating the informational value of stress tests in reducing bank opacity. This supervisory “toolkit” is considered extremely important, as it provides meaningful insights to the supervisors of the banking institutions and the market stakeholders by improving the transparency of the financial sector, allowing them to segregate banks more effectively.

This study constitutes one of the earliest attempts to shed light on the financial and information role of the European supervisory stress tests by comparing the EU-wide 2018 and the EU-wide 2021 stress test exercises. Moreover, it provides concrete empirical evidence and qualitative analysis to explore certain aspects of the European and US stress tests.

This paper aims to present a conceptual framework of how software teams can leverage the implicit information of implemented acceptance tests to cater to the needs of decision makers. The research questions on this framework were how business stakeholders can receive project status information in an intuitive way and how this framework can guarantee the traceability of tests to requirements.

The conceptual framework delineates the design of an acceptance test framework in three aspects: how the requirements model reflects the evolving states of requirement maturity over a project, how the acceptance test model becomes synchronized with the requirements model without a traceability matrix and how the acceptance test model communicates business value to the decision makers.

In an industrial case study, the presented framework yielded the positive effects of intuitive understanding by business stakeholders, high test coverage of requirements and distinctly reduced manual quality assurance (QA) work by automated testing for browsers and mobile devices.

The presented framework can help to convince business stakeholders to approve the budget for building a testing framework because it delivers them value as a status reporting tool.

This paper is the first to describe a step-by-step approach to solving a critical problem that IT departments frequently face. The solution consists in a new way of transforming the perception of a technical framework into a reporting tool for business information by intuitive design. The idea of mapping hierarchically corresponding abstraction layers can be transferred to other engineering domains.

The purpose of this paper is to give an overview of variability of empirical results of several financial contagion studies, taking into account the role of financial markets, data sets and the applied definitions and methods that may explain the variability of empirical evidence.

The authors used qualitative analysis of published research materials about previous financial crises and analyzed the variability of empirical results of around 75 studies of financial contagion, taking into account the particularities of financial markets, data sets and tests methods.

The results of the analysis show that empirical studies provide heterogeneous results depending on applied definitions and methods, as well as chosen crises, destination countries and financial indices. Summing up all the relevant empirical findings the results supporting the contagion hypothesis are in clear dominance, but taking into account differences in definitions and testing methodologies the research did not reveal clear results as to which evidence dominates or should dominate.

The authors conclude that solely qualitative analysis of published research materials about previous financial crises does not give sufficient information to elaborate proper management measures to prevent serious consequences of financial crises. The authors propose that it is possible to obtain a more adequate picture of financial contagion by using a meta‐analysis, which the authors are planning to do in future studies.

The paper provides information about some reasons that explain the variability of the results that are presented in the empirical studies about financial contagion. This information can be used for elaborating policy proposals and regulations that can help alleviate possible negative consequences of financial contagion. The paper shows the way for future articles summarising financial contagion.

The study sums up previous findings on the field of financial contagion and shows the insufficiency of the traditional literature review to accomplish that task.

This paper aims on a methodology to overcome the fact that conventional service life testing of porous journal bearings (PJBs) requires long test times and is not economical.

This paper sketches out a pathway to strongly accelerated life tests for PJBs enabled by high load and elevated temperature, which saves months or even years of testing. The testing time is not only reduced to a few weeks, but the results are also statistically secured via a multiple test rig construction of a custom-made tribometer.

An exemplary bearing-lubricant combination is tested in the mixed lubrication regime, where the coefficient of friction is monitored during the test.

A Weibull curve is fitted to the experimental results to show the survival probability of the combination over time.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0351/

This paper aims to gauge developers’ perspectives regarding the participation of the public and anonymous crowd testers worldwide, with a range of varied experiences. It also aims to gather their needs that could reduce their concerns of dealing with the public crowd testers and increase the opportunity of using the crowdtesting platforms.

An online exploratory survey was conducted to gather information from the participants, which included 50 mobile application developers from various countries with diverse experiences across Android and iOS mobile platforms.

The findings revealed that a significant proportion (90%) of developers is potentially willing to perform testing via the public crowd testers worldwide. This on condition that several fundamental features were available, which enable them to achieve more realistic tests without artificial environments on large numbers of devices. The results also demonstrated that a group of developers does not consider testing as a serious job that they have to pay for, which can affect the gig-economy and global market.

This paper provides new insights for future research in the study of how acceptable it is to work with public and anonymous crowd workers, with varying levels of experience, to perform tasks in different domains and not only in software testing. In addition, it will assist individual or small development teams who have limited resources or who do not have thousands of testers in their private testing community, to perform large-scale testing of their products.