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The purpose of this paper is to investigate the relationships between technology orientations and export performance of small and medium-sized enterprises (SMEs).

A quantitative research design was adopted for this study. The paper formulates hypotheses from the literature review. These hypotheses are tested using structural equation modeling with data collected from 231 SMEs in Uganda. Data were analyzed using SPSS version 23 and AMOS.

The findings of this study showed technology orientation has a positive and significant relationship with the performance of Ugandan SMEs and that supply chain agility moderates technology orientation and export performance.

The study discusses the findings, advances limitations and managerial implications. It also suggests future research avenues. It proposes some recommendations to help Ugandan SMEs to form flexible supply chains, use the latest technology and create strong relationship ties with their partners in the supply chain.

The study suggests that managers of Ugandan SMEs should use the latest technology in production, marketing, logistics and supply chain management which will enable them to respond quickly to customer tastes and preferences leading to higher levels of export performance.

This study contributes to the literature on strategic management showing the reliability of scales used and the confirmatory of the factor structure. This study shows that in strategic management technology, orientation is critical in increasing export performance. This study has extended the resource-based view (RBV) and dynamic capabilities theories.

This paper aims to shed light on features of successful innovation and on the role played by downstream open innovation (OI) dynamics in the Fast Moving Consumer Goods (FMCG) industry. It also explores the reasons for the decline in the number of disruptive innovations in this industry in the European Union (EU).

The authors interpret the data in a Kantar consumer panel dataset on disruptive innovations in Spain through an exploratory research including in-depth interviews with 19 managers in the industry.

Results show that downstream open innovation in this industry is mostly limited to the executional stage in the process and highlight the crucial role played by the point of purchase in the success of innovations. The authors build up a virtuous circle of innovation based on features such as the use of OI processes, company focus and marketing support, transparency and collaboration with retailers, as well as the product's uniqueness and its potential to become viral.

The paper focuses on Spain and, thus, results cannot be generalised. Further research in other countries would be interesting.

The study describes the features of disruptive innovators and develops an extensive list of success factors.

The development of disruptive innovation is a source of competitive advantages and one of the most relevant activities of managers today. Nevertheless, the number of disruptive innovations is in decline, and only a few succeed, negatively affecting consumer welfare.

Through this study, the authors provide insights on the features of successful innovators in FMCGs and describe the factors affecting the decreasing trend in the number of breakthrough innovations. Further, this paper fulfils an identified need to study OI in low-tech industries.

This study attempts to investigate the interrelationship between choice-based educational achievement and employability prospects across the skill-based occupations amongst the youth in India.

This study relies on the use of National Sample Survey (NSS) data on employment and unemployment for the 68th round (2011–2012) and the Periodic Labour Force Survey (PLFS) (2017–2018). To estimate the relative contributions of choice-based educational attainment affecting the skill-based employment of youth in a different category of occupations ( high/medium/low skilled), the multinomial logistic regression and its marginal effects have been used.

The study finds educational attainment both as an opportunity (improvising employability in the high and medium skill occupation) and a challenge (highest unemployment amongst the educated) while ensuring skill-based youth employability. Despite the growing enrolment of youth in education, youth from a general education background does not find sustained employability prospects in high-skill occupations.

Vocational education highlights a brighter employability prospect but the acceptability of the same amongst the youth needs a policy intervention.

Educational choices need an intervention based on market-driven apprenticeships and training.

The decline of overall employability in the low-skill occupation raises a threat to inclusive development as such youth results to Not in Employment, Education or Training (NEET), better identified as the unproductive economic youth.

This study attempts to investigate that “how far the choice of educational attainment (general/technical/vocational) is able to make youth a fit in the world of work?” in the Indian context, where the youth constitute the highest share in the population.

Collaboration and operational capabilities are two strengths for managing supply chains to achieve operational performance. In this context, this study aims to analyze the mediating effect of operational capabilities on the relationship between collaborative supply chain management and operational performance.

The study design consisted of a theoretical framework to estimate the mediation paths by latent variable structural modeling methods. A survey of 138 respondents from Brazilian capital goods companies was conducted.

The study revealed that operational capabilities partially mediate the relationship between collaborative supply chain management and operational performance. The findings provide important guidance for managers to strengthen the relationship with suppliers to continuously improve operational capability.

As the sample size was made up of 138 respondents, it was impossible to revalidate the theoretical–empirical model. New data need to be collected to re-evaluate the structural model and expand them to other economic segments.

By examining the theoretical insights and empirical findings, the study expanded knowledge about collaborative management and the understanding of the importance of operational capabilities in the relationship between collaborative management and operational performance for management practices.

The study developed a theoretical–empirical measurement model, reliable and statistically validated, to test the mediating effect of operational capabilities in the relationship between collaborative management and operational performance.

The COVID-19 pandemic has wrought havoc on economies around the world. The purpose of this study is to learn about the distributional impacts of the pandemic.

The authors contribute new theoretical and empirical evidence on the distributional impacts of the pandemic on different income groups in a multicountry setting. The authors analyze rich individual-level survey data covering 6,082 respondents from China, Italy, Japan, South Korea, the United Kingdom and the United States. The results are robust to various econometric models, including ordinary least squares (OLS), Tobit and ordered probit models with country-fixed effects.

The authors find that while the outbreak has no impact on household income losses, it results in a 63% reduction in the expected own labor income for the second-poorest income quintile. The pandemic impacts are most noticeable for savings, with all the four poorer income quintiles suffering reduced savings ranging between 5 and 7% compared to the richest income quintile. The poor are also less likely to change their behaviors regarding immediate prevention measures against COVID-19 and healthy activities. The authors also found countries to exhibit heterogeneous impacts.

Designing tailor-made social protection and health policies to support the poorer income groups in richer and poorer countries can generate multiple positive impacts that help minimize the negative and inequality-enhancing pandemic consequences. These findings are relevant not only for COVID-19 but also for future pandemics.

The authors theoretically and empirically investigate the impacts of the pandemic on poorer income groups, while previous studies mostly offer empirical analyses and focus on other sociodemographic factors. The authors offer a new multicountry analysis of several prevention measures against COVID-19 and specific health activities.

In this paper, an emerging state-of-the-art machine intelligence technique called the Hierarchical Temporal Memory (HTM) is applied to the task of short-term load forecasting (STLF). A HTM Spatial Pooler (HTM-SP) stage is used to continually form sparse distributed representations (SDRs) from a univariate load time series data, a temporal aggregator is used to transform the SDRs into a sequential bivariate representation space and an overlap classifier makes temporal classifications from the bivariate SDRs through time. The comparative performance of HTM on several daily electrical load time series data including the Eunite competition dataset and the Polish power system dataset from 2002 to 2004 are presented. The robustness performance of HTM is also further validated using hourly load data from three more recent electricity markets. The results obtained from experimenting with the Eunite and Polish dataset indicated that HTM will perform better than the existing techniques reported in the literature. In general, the robustness test also shows that the error distribution performance of the proposed HTM technique is positively skewed for most of the years considered and with kurtosis values mostly lower than a base value of 3 indicating a reasonable level of outlier rejections.