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The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

To remain sustainable, open source software (OSS) projects must attract new members—or newcomers—who make contributions. In this paper, the authors develop a set of hypotheses based on the knowledge barriers framework that examines how OSS communities can encourage contributions from newcomers.

Employing longitudinal data from the source code repositories of 232 OSS projects over a two-year period, the authors employ a Poisson-based mixed model to test how community characteristics, such as the main drivers of knowledge-based costs, relate to newcomers' contributions.

The results indicate that community characteristics, such as programming language choice, documentation effort and code structure instability, are the main drivers of knowledge-based contribution costs. The findings also suggest that managing these costs can result in more inclusive OSS communities, as evidenced by the number of contributing newcomers; the authors highlight the importance of maintaining documentation efforts for OSS communities.

This paper assumes that motivational factors are a necessary but insufficient condition for newcomer participation in OSS projects and that the cost to participation should be considered. Using the knowledge barriers framework, this paper identifies the main knowledge-based costs that hinder newcomer participation. To the best of the authors' knowledge, this is the first empirical study that does not limit data collection to a single hosting platform (e.g., SourceForge), which improves the generalizability of the findings.

The purpose of this paper is to develop a prototype of a wearable medical device in the form of a bandage with a real-time data monitoring platform, which can be used domestically for diabetic patients to identify the possibility of foot ulceration at the early stage.

The prototype can measure blood volumetric change and temperature variation in the forefoot area simultaneously. The waveform extracted using a pulsatile-blood-flow signal was used to assess blood perfusion-related information, and hence, predict ischemic ulcers. The temperature difference between ulcerated and the reference was used to predict neuropathic ulcers. The medical device can be used as a bandage during the application wherein the sensory module is placed inside the hollow pocket of the bandage. A platform was developed through a mobile application where doctors can extract real-time information, and hence, determine the possibility of ulceration.

The height of the peaks in the pulsatile-blood-flow signal measured from the subject with foot ischemic ulcers is significantly less than that of the subject without ischemic ulcers. In the presence of ischemic ulcers, the captured waveform flattens. Therefore, the blood perfusion from arteries to the tissue of the forefoot is considerably low for the subject with ischemic ulcers. According to the temperature difference data measured over 25 consecutive days, the temperature difference of the subject with neuropathic ulcers occasionally exceeded the 4 °F range but mostly had higher values closer to the 4 °F range. However, the temperature difference of the subject who had no complications of neuropathic ulcers did not exceed the 4 °F range, and the majority of the measurements occupy a narrow range from −2°F to 2 °F.

The proposed prototype of wearable medical apparatus can monitor both temperature variation and pulsatile-blood-flow signal on the forefoot simultaneously and thereby predict both ischemic and neuropathic diabetes using a single device. Most importantly, the wearable medical device can be used domestically without clinical assistance with a real-time data monitoring platform to predict the possibility of ulceration and the course of action thereof.

The intention of the empirics is to contribute to the general understanding of investor responses to market price shocks. The authors review assumptions about investor behavior in response to price shocks and investigate alternative rebalancing heuristics.

The authors use market data over 40 years to define market shocks. Portfolio rebalancing implements constrained Markowitz mean-variance (MV) heuristics.

Momentum rebalancing in portfolio management outperforms contrarian rebalancing in the study interval. Sensitivity analysis by decade, sector constraints and proportion of security holdings bought or sold continue to support momentum rebalancing.

The results are consistent with under-responding to price shocks at consensus levels in financial markets. The theoretical background provides a basis for experimental lab studies of shocks of different magnitudes under conditions in which participants have information on the levels of other participants and a condition in which they can only observe their previous estimates.

Managing portfolios in the face of price disturbances of different magnitudes is informed by empirical studies and their implications for investor behavior.

This is the first study the authors can locate that uses market data with alternative rebalancing heuristics to estimate price returns from the respective heuristics over a time interval of 40 years. The authors support the results with sensitivity estimates and consider implications for the underlying agent heuristics in light of background studies.

We develop a credit-risk model to study the informational role of investment in an economy susceptible to large liquidity shocks. Firms' investment decisions carry information about their asset quality, thereby mitigating informational frictions when firms enter bankruptcy. An increase in aggregate investment can reduce the informational value of investment, depressing firms' recovery values. Therefore, policies boosting investment can decrease debt and firm values by reducing the informational value of investment. The presence of debt overhang may enhance firm value by making firms' investment decisions more informative. We present suggestive empirical evidence consistent with model predictions on the relation between firms' investments and recovery rates.

With the evolution of the turbulent environment constantly triggering the emergence of a trust crisis between organizations, how can university–industry (U–I) alliances respond to the trust crisis when conducting green technology innovation (GTI) activities? This paper aims to address this issue.

The authors examined the process of trust crisis damage, including trust first suffering instantaneous impair as well as subsequently indirectly affecting GTI level, and ultimately hurting the profitability of green innovations. In this paper, a piecewise deterministic dynamic model is deployed to portray the trust and the GTI levels in GTI activities of U–I alliances.

The authors analyze the equilibrium results under decentralized and centralized decision-making modes to obtain the following conclusions: Trust levels are affected by a combination of hazard and damage (short and long term) rates, shifting from steady growth to decline in the presence of low hazard and damage rates. However, the GTI level has been growing steadily. It is essential to consider factors such as the hazard rate, the damage rate in the short and long terms, and the change in marginal profit in determining whether to pursue an efficiency- or recovery-friendly strategy in the face of a trust crisis. The authors found that two approaches can mitigate trust crisis losses: implementing a centralized decision-making mode (i.e. shared governance) and reducing pre-crisis trust-building investments. This study offers several insights for businesses and academics to respond to a trust crisis.

The present research can be extended in several directions. Instead of distinguishing attribution of trust crisis, the authors use hazard rate, short- and long-term damage rates and change in marginal profitability to distinguish the scale of trust crises. Future scholars can further add an attribution approach to enrich the classification of trust crises. Moreover, the authors only consider trust crises because of unexpected events in a turbulent environment; in fact, a trust crisis may also be a plateauing process, yet the authors do not study this situation.

First, the authors explore what factors affect the level of trust and the level of GTI when a trust crisis occurs. Second, the authors provide guidelines on how businesses and academics can coordinate their trust-building and GTI efforts when faced with a trust crisis in a turbulent environment.

First, the interaction between psychology and innovation management is explored in this paper. Although empirical studies have shown that trust in U–I alliances is related to innovation performance, and scholars have developed differential game models to portray the GTI process, building a differential game model to explore such an interaction is still scarce. Second, the authors incorporate inter-organizational trust level into the GTI level in university–industry collaboration, applying differential equations to portray the trust building and GTI processes, respectively, to reveal the importance of trust in CTI activities. Third, the authors establish a piecewise deterministic dynamic game model wherein the impact of crisis shocks is not equal to zero, which is inconsistent with most previous studies of Brownian motion.