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A hidden enemy of distribution efficiency is at work in almost all distribution systems. It causes increased distribution costs, yet, in many firms, seldom receives much management attention. Who, or what, is this hidden enemy? Quite simply, it is goods which require return to the vendor or adjustment of sales terms once they have been received by a customer.

Dramatic increase in international trade during the past two decades and increasing political instability of the third world countries have forced the multinational firms to devote more time and resources to risk assessment. In the past decade we have witnessed that international business can be affected by wars, revolutions, coup d'etats, social unrest, third world debt crisis, and terrorism. Some firms have been forced out of the third world countries without a reasonable compensation.

This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the non-holonomic vehicle tracking problem with the lower computational load and the convergence performance.

A fusion event-triggered model predictive control version is developed in this paper. The authors designed a shrinking prediction strategy.

The fusion event-triggered model predictive control scheme combines the strong points of event triggered and self-triggered methods. As the practical state approaches the terminal set, the computational complexity of optimal control problem (OCP) decreases.

The proposed strategy has proven to stabilize the system and also guarantee a reproducible solution for the OCP. Also, it is proved to be effected by the performance of the simulation results.

This study proposes the Smart SME Technology Readiness Assessment (SSTRA) methodology which aims to enable practitioners to assess the SMEs Industry 4.0 technology readiness throughout the end-to-end engineering across the entire value chain; the smart product design phase is the focus in this paper.

The proposed SSTRA utilises the analytic hierarchy process to prioritise smart SME requirements, a graphical interface which tracks technologies' benchmarks under Industry 4.0 Technology Readiness Levels (TRLs); a mathematical model used to determine the technology readiness and visual representation to understand the relative readiness of each smart main area. The validity of the SSTRA is confirmed by testing it in a real industrial environment. In addition, the conceptual model for Smart product design development is proposed and validated.

The proposed SSTRA offers decision-makers the facility to identify requirements and rank them to reflect the current priorities of the enterprise. It allows SMEs to assess their current capabilities in a range of technologies of high relevance to the Industry 4.0 area. The SSTRA assembles a readiness profile allowing decision-makers to not only perceive the overall score of technology readiness but also the distribution of technology readiness across the main smart areas. It helps to visualise strengths and weaknesses; whilst emphasising the fundamental gaps that require serious action to assist the program with a well-balanced effort towards a successful transition to Industry 4.0.

The SSTRA provides a step-by-step approach for decision-making based on data collection, analysis, visualisation and documentation. Hence, it greatly mitigates the risk of further Industry 4.0 technology investment and implementation.

This study aims to examine the patterns of and factors influencing agricultural diversification among farmers in the Kaithal district of Haryana, India.

The authors analysed the data collected from a sample of 400 agricultural households from five blocks of Kaithal, Haryana. Agricultural diversification is measured through the Herfindahl Index. Determinants of agricultural diversification have been evaluated using the two-stage least square method.

The average value of the diversification index among farmers in Kaithal is 0.51, indicating that there is room for diversification. In the study area wheat and rice are the dominant crops, while vegetables emerge as the most common non-staple crop. Regression analysis indicates that farmers of Scheduled Caste (SC) are more inclined to diversify crops. Factors such as larger land ownership, utilization of tractors, government subsidies, education and loans positively impact agricultural diversification. The availability of irrigation facilities, and employing labour negatively influence it.

Focus on SC within the diversification policies for equitable access to resources. Special programmes aimed at educating small landowners and casual labourers about diversified crops. Implementing an “Uberisation” model for tractors, providing subsidies on seeds and equipment, customized financing programmes tailored to the needs of small-scale farmers can contribute to boosting agricultural diversification.

This study contributes by providing insights into the farm-level determinants of agricultural diversification in Kaithal district, Haryana. It adds to the understanding of factors influencing agricultural diversification in developing economies at the micro level.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2023-0963.