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Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they perceive change to be taking place. This study aims to analyse how African indigenous vegetable (AIV) farmers perceive climate change in three different agro-climatic zones (ACZs) in Kenya, identify the main differences in historical seasonal and annual rainfall and temperature trends between the zones, discuss differences in farmers’ perceptions and historical trends and analyse the impact of these perceived changes and trends on yields, weeds, pests and disease infestation of AIVs.

Data collection was undertaken in focus group discussions (FGD) (N = 211) and during interviews with individual farmers (N = 269). The Mann–Kendall test and regression were applied for trend analysis of time series data (1980-2014). Analysis of variance and least significant difference were used to test for differences in mean rainfall data, while a chi-square test examined the association between farmer perceptions and ACZs. Coefficient of variation expressed as a percentage was used to show variability in mean annual and seasonal rainfall between the zones.

Farmers perceived that higher temperatures, decreased rainfall, late onset and early retreat of rain, erratic rainfall patterns and frequent dry spells were increasing the incidences of droughts and floods. The chi-square results showed a significant relationship between some of these perceptions and ACZs. Meteorological data provided some evidence to support farmers’ perceptions of changing rainfall. No trend was detected in mean annual rainfall, but a significant increase was recorded in the semi-humid zone. A decreasing maximum temperature was noted in the semi-humid zone, but otherwise, an overall increase was detected. There were highly significant differences in mean annual rainfall between the zones. Farmers perceived reduced yields and changes in pest infestation and diseases in some AIVs to be prevalent in the dry season. This study’s findings provide a basis for local and timely institutional changes, which could certainly help in reducing the adverse effects of climate change.

This is an original research paper and the historical trends, farmers’ perceptions and effects of climate change on AIV production documented in this paper may also be representative of other ACZs in Kenya.

The purpose of this study was to assess the knowledge of head and neck cancers (HNCs), their risk factors, signs and symptoms among the general public of Karachi, Pakistan.

Initially, 503 individuals were approached for data collection, out of which 404 fit the inclusion criteria (response rate = 80.03%). Nonprobability convenience sampling was utilized to select participants who fell under the age group of 15–60 years, barring the fields of Bachelor of Medicine and Bachelors of Surgery (MBBS) and Bachelors of Dentistry (BDS). Knowledge was evaluated by a 9-item questionnaire, the scores of which yielded the following interpretations: No (0), low (1–3), moderate (4–6) and high (7–9) knowledge.

Of the 404 participants who completed the questionnaire, 357 (88.4%) participants claimed to be aware of HNC. The HNC knowledge scores had a statistical relevance with socioeconomic status (p = <0.01) and level of education (p = 0.02). Most participants recognized a “lump or swelling in the throat” (87.1%) as the most common symptom, followed by “bleeding in mouth or throat” (84.7%). Surprisingly, 75.25% of participants thought HNCs were inclusive of brain cancer.

Overall, knowledge of HNCs among the general public of Karachi surpasses the knowledge in other regions around the world. Our study demonstrated that people indulge in unhealthy habits despite having sufficient knowledge and this warrants prompt interventions and counseling of the people.

The purpose of this qualitative study is to explore well-being experiences of international business travellers (IBTs) and contribute to our understanding of personal and job characteristics as antecedents of ill- or well-being.

The authors’ insights are based on semi-structured in-depth interviews with 32 IBTs assigned to various destinations ranging from single-country travel to global operation. Participants in this study represent a range of traveller personas (regarding demographics, type of work, travel patterns). Thematic analysis is used to reveal new insights.

The authors’ analysis revealed trip-load (i.e. workload, control, organisational support) and intensity of travel (i.e. frequency, duration and quality) as job characteristics that sit on an energy stimulation continuum, driving work-related outcomes such as stress and burnout or health and well-being. Energy draining and boosting processes are moderated by cognitive flexibility and behavioural characteristics.

Findings represent a framework for managing IBT well-being via adjustments in job and travel characteristics, plus guidance for training and development to help IBTs self-manage.

The insights within this paper contribute to the conversation around how to enhance well-being for IBTs and frequent flyers. The study intends to offer direction as to which specific job, psychological and behavioural characteristics to focus on, introducing a novel framework for understanding and avoiding serious consequences associated with international mobility such as increased stress, burnout and ill-health.

This study examines the relationship of positive career shocks and career optimism. The mediating role of career decision-making self-efficacy (CDSE) between positive career shocks and career optimism and the moderating role of consideration of future consequences – immediate (CFC-I) between CDSE and career optimism are checked.

Through cluster sampling, cross-sectional data from 192 professionals of electronic media industry were collected via an electronically administered questionnaire. For preliminary descriptive data analysis, SPSS version 21 was used. SmartPLS version 3.0 was used for testing the proposed hypotheses.

The results showed that positive career shocks have a relationship with career optimism via CDSE. Also, CFC-I moderated the relationship of CDSE and career optimism such that the relationship of CDSE and career optimism was stronger at higher level of CFC-I.

The study provides implications for the career consultants, human resource professionals and senior management of organizations. All these stakeholders can strive to build an inventory of positive career shocks. Also, shifting to a surprised business model of announcing compensations and promotions is another area to work on. The results of this study further suggest disengaging the fresh potential employees in the initial processes of recruitment. Interdepartmental coordination of health and safety department and human resource management department is also a very important implication for this study to highlight the positive aspects of being optimistic.

The study is among the few empirical studies which investigates the relationship between positive career shocks and career optimism via CDSE. Also, in light of the latest call of various empirical works in the domain, this study adds a moderating variable, i.e. CFC-I in predicting career optimism. Furthermore, contrary to the conventional approach of applying students' data on career models, this study tests the proposed career model on data collected from professionals.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Among the many factors fueling the inflationary tendencies in an economy such as monetary shocks, structural shocks, demand shocks, external shocks and demographic changes, the issue of inflation (INF) has also been found to be related to fiscal policy decisions of the government. The purpose of this study is to investigate the inflationary tendencies in India particularly from the fiscal point of view. The study also examines the influence of other potential determinants such as output growth rate, interest rate, trade-openness (TO) and oil price inflation (OPI).

To examine the dynamic nature of association between fiscal deficit and inflation, the study applies the Toda-Yamamoto (1995) test and Breitung and Candelon (2006) test to investigate the nature of causality in time and frequency domain frameworks. In addition, to scrutinize the possibility of a long-run association, that too from an asymmetric point of view, the study applies a Non-linear Autoregressive Distributed lag model (NARDL) given by Shin et al. (2014). Finally, non-linear cumulative dynamic multipliers are used to trace the traverse between disequilibrium position of short-run and subsequent long-run equilibrium of the system.

The authors found a unidirectional causality from fiscal deficit to inflation in case of time domain analysis and no feedback causality is reported. However, in case of frequency domain design, causality from fiscal deficit to inflation is found at low frequencies only, i.e. no short-run causality is established and hence dynamic nature of the relationship between the two variables is vindicated. Using NARDL model, the results document the existence of an asymmetric long-run direct association between fiscal deficit and inflation. However, an increase in deficit is found to be more inflationary and a decrease affects the inflation with a lower magnitude. The asymmetric impact of fiscal deficit on inflation can be explained through the existence of liquidity constraints, consumption-investment downward inflexibility and the downward price stickiness. Contractionary monetary policy action is found to be more effective than an expansionary one, signifying the asymmetric influence of monetary policy actions on the inflation of India. Similarly, in a supply-constrained economy with downward price rigidity, the authors found an asymmetric impact of output growth and output decline on inflation. As regard to the trade-openness, although an asymmetry is reported, the signs refute the validation of Romer (1993) hypothesis. Finally, the impact of oil price inflation on the inflationary pressures is according to theory but the coefficients are devoid of statistical significance.

These results indicate some important policy recommendations. Fiscal consolidation strategy should be executed in an appreciable manner to achieve the sound fiscal health and lower INF. The disciplined fiscal strategy would also be imperative for an effective monetary policy. Monetary authorities should possess noticeable credibility to manage the macroeconomic system and policy stances should be implemented according to requirements of the economy. Growth in output should be encouraged to have two-fold benefits to the economy – reducing INF on the one hand and fiscal deficits on the other.

The study contributes to the existing literature in the following ways. First, taking note of dynamic nature of the relationship between these two variables, the study examined the deficit INF nexus in a dynamic and asymmetric framework. The novelty of the study is ensured by the very nature of it is the first study in case of India to identify the fiscal INF in an asymmetric configuration. The authors applied a NARDL model, given by Shin et al. (2014) to examine the existence of any cointegrating relationship in an asymmetric paradigm. Second, the nature of causality between fiscal deficit and INF has been examined in a time domain and FD framework to portray precisely the casual interactions between these two variables in the short-run and long run. The study will, therefore, enrich the existing literature along the asymmetric lines.

Polyvictimization means looking at multiple victimizations of different kinds that one person has experienced. Virtually, all of the work in this field focuses on the effects of childhood trauma and victimization on currently distressed children, and empirical and theoretical work on the intertwining of adult female offline and online abuse experiences is in short supply. Recently, however, some scholars are starting to fill these research gaps by generating data showing that technology-facilitated violence and abuse are part and parcel of women's polyvictimization experiences at institutions of higher education. This chapter provides an in-depth review of the extant social scientific literature on the role technology-facilitated violence and abuse plays in the polyvictimization of female college/university students. In addition to proposing new ways of knowing, we suggest progressive policies and practices aimed at preventing polyvictimization on the college campus.

While the three lines model (TLM) provides an organizational structure to execute risk and control duties, research and practice show limitations in the model's implementation. These limitations result in governance issues. Such issues, together with control weaknesses, could be addressed by leveraging properties of distribution, transparency, and immutability of blockchain technology. To this end, in this paper the authors propose a conceptual control framework based on blockchain technology to augment control practice.

The design of the resulting blockchain-based control framework (BBCF) and its prototype, based on the design science research methodology (DSRM), is presented and discussed in terms of the potential impact in the context of the identified problems within the TLM.

One potential outcome of BBCF could be to redefine the scope and boundaries of some of the activities in audit and control practices from a more static to a more dynamic and prospective role. In a larger context of improving governance practices, the BBCF could set the path for a more inclusive and participatory interaction between the different governance actors of an organization.

However, this assumes that blockchain is more widely adopted despite its complexity and rigidity.

BBCF covering both a conceptual model design and a reference implementation provides an innovation in audit and control. BBCF could include all relevant stakeholders who have an interest in corporate governance and control activities, including the regulators.

The contribution intends to serve both as a starting point for discussing the evolution of audit and control practice based on blockchain technology, as well as an initial actionable prototype for experimentation and further development.

The paper compares multi-period forecasting performances by direct and iterated method using Bayesian vector autoregressive (VAR) models.

The paper adopts Bayesian VAR models with three different priors – independent Normal-Wishart prior, the Minnesota prior and the stochastic search variable selection (SSVS). Monte Carlo simulations are conducted to compare forecasting performances. An empirical study using US macroeconomic data are shown as an illustration.

In theory direct forecasts are more efficient asymptotically and more robust to model misspecification than iterated forecasts, and iterated forecasts tend to bias but more efficient if the one-period ahead model is correctly specified. From the results of the Monte Carlo simulations, iterated forecasts tend to outperform direct forecasts, particularly with longer lag model and with longer forecast horizons. Implementing SSVS prior generally improves forecasting performance over unrestricted VAR model for either nonstationary or stationary data.

The paper finds that iterated forecasts using model with the SSVS prior generally best outperform, suggesting that the SSVS restrictions on insignificant parameters alleviates over-parameterized problem of VAR in one-step ahead forecast and thus offers an appreciable improvement in forecast performance of iterated forecasts.