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The purpose of this paper is to study the production methods and potential of self-help groups (SHGs) for linking to micro, small and medium enterprises (MSME) in the Union Territory of Puducherry region.

The variables for the research work were identified through a literature review relating to SHGs production methods and 251 primary data were collected through the random sample using the survey method. The statistical software of IBM-SPSS was used to analyze the data using the statistical methods of descriptive statistics like frequency analysis simple mean and inferential statistics such as chi-square, correspondence analysis, correlation and ANOVA test.

The majority of SHGs consisting of 49.8% are willing to pay an amount up to Rs. 5,000 if training is provided through MSME organizations, a higher number of SHGs have indicated that they are very much interested in ancillary production activities, 35.5% of SHGs are using no machines and ANOVA test result shows that there is a significant difference between numbers of years of functioning with respect to production activity.

The authors have selected the Union Territory of Puducherry was taken as the sample region of the study due to its high rural poverty levels of 16.9%.

The research study endeavors to study the various production methods and preferences of SHGs and it will be of immense utility to the government, banks, microfinance organizations and other policymakers.

Existing literature reviews are conducted on various problems in service and manufacturing sectors, it is essential to conduct empirical research on an inclusive sector like SHG production activities and preferences in emerging economies like India.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

Crowdfunding (CF) has become an increasingly popular means of financing for entrepreneurs and has attracted significant attention from both researchers and practitioners in recent years. The purpose of this study is to investigate the core content and knowledge diffusion paths in the CF field. Specifically, we aim to identify the main topics and themes that have emerged in this field and to trace the evolution of CF knowledge over time.

This study employs co-word clustering and main path analysis (MPA) to examine the historical development of CF research based on 1,528 journal articles retrieved from the Web of Science Core Collection database.

The results of the analysis reveal that CF research focuses on seven themes: sustainability, entrepreneurial finance, entrepreneurship, fintech, social entrepreneurship, social capital, and microcredits. The analysis of the four main paths reveals that equity CF has been the dominant topic in the past years. Recently, CF research has tended to focus on topics such as fintech, the COVID-19 pandemic, competition, Brexit, and policy response.

To the authors' best knowledge, this is the first attempt to explore knowledge diffusion dynamics in the CF field. Overall, the study offers a structure for analyzing the paths through which knowledge is diffused, enabling scholars to effectively manage a large volume of research papers and gain a deeper understanding of the historical, current, and future trends in the development of CF.

Lean management is a contemporary management system that firms adopt to boost their performance. Lean management can be integrated with human resources management to develop a new concept of lean human resources management (LHRM). This entails the implementation of several practices. However, the LHRM–performance paradigm remains underexplored in the literature. Hence, this study aims to examine the interrelationships between LHRM practices and the impacts of those practices on firm performance (FP).

Using two equal-sized samples (n = 250 each) of manufacturing firms in Jordan and Germany, this study proposes two structural equation models (i.e. a Jordanian and a German models) depicting the interrelationships between LHRM practices and the impacts of those practices on FP. After testing these models, a comparison between them is conducted, producing findings with theoretical and practical implications.

The main findings of this study indicate that the average implementation of LHRM practices among German manufacturing firms is at a higher level than the average implementation among Jordanian firms. The findings also support the proposed interrelationships between LHRM practices and the impact of those practices on FP for both the Jordanian and German models.

To the best of the authors’ knowledge, this study is among the first to highlight the proposed relationships, both in general and in the context of comparing developed and developing countries. Its findings have important implications that can enable manufacturing managers to benefit from the implementation of LHRM practices to enhance FP in different contexts. These findings provide valuable insights for human resource managers and decision-makers and open several avenues for future research.

The purpose of this study is to increase the resilience capacity of residential health-care professionals to achieve intrapreneurial development in workers. Through training based on the development of emotional competencies and the application of mindfulness techniques, the aim is for the individual to become aware of his or her role, learn to manage emotions and reduce feelings of distress and anxiety.

The proposed programme has a duration of eight weeks. Every four days of training, mindfulness sessions are integrated, and at the beginning and end of the working day, 10 min are spent with superiors to give feedback on what happened during the day and the setting of new objectives. A control group is also established where they do not undergo such training. After the delivery of the programme, the results obtained after the application of the methodology to a sample of 91 residential health-care professionals are presented. By means of a validated resilience questionnaire composed of 25 items, the aim is to measure the resilience capacity of the participants before and after training and to observe the impact of the programme.

The results of this study show that the training has led to an improvement in the overall resilience capacity by 3.93% and has been able to reduce the existing gap between those over 45 years of age and younger people, although the age-related variable still represents a significant difference.

This study provides an innovative way of fostering entrepreneurship. While participants work on resilience management through mindfulness techniques, organisational commitment is achieved.

The purpose of this paper is to investigate the effect of trust with suppliers on hospital-supplier integration (SI) and hospital supply chain (SC) performance. Additionally, the mediating effect of SI on trust-hospital SC performance is investigated.

A research model and hypotheses were developed based on literature review. The study is based on survey data collected from 152 respondents in 55 private hospitals in Jordan. The proposed hypotheses were tested using structural equation modeling.

The paper finds that trust with suppliers has a positive impact on hospital-SI and hospital SC performance. Hospital-SI partially mediates the relationship between trust and hospital SC performance.

The findings of this research provide useful insights into the role of trust in boosting SC performance in the healthcare sector. High levels of SI not only improve hospital SC performance but also enhance the transformation of trust benefits into SC performance.

This research is one of the limited studies that investigated the effect of trust on hospital-SI and hospital SC performance in the healthcare sector. To the best of the authors’ knowledge, this is the first study to investigate those relationships in the Middle East in general and in Jordan in particular.

There is evidence in the literature suggesting the usage of performance measurement framework (PMF) has a positive impact on organisational performance. This is in line with resource based view (RBV) theory, which argues attaining competitive advantage through internal resources and capabilities. In this regard, PMF can be viewed as a “resource” that can be explored in enabling organisational performance. This paper is aimed at developing PMF for the oil and gas supply chain (SC) as a resource and strategic capability.

Drawing on RBV theory, a questionnaire survey was designed based on prior literature review and exploratory interview with five SC experts. Following this, the questionnaires were distributed to 550 companies in the UK and 120 companies in Malaysia, which resulted in 15% overall response rate.

This study presents the prevalence of performance measures (PM) for the oil and gas industry based on the level of importance. It also reveals the impact of the usage of PMF on overall organisational performance. In addition, it identifies the challenges in managing SC performance and factors to be considered in choosing PM.

This study identifies the challenges in managing SC performance and establishes distinctive factors to consider when choosing PM in the oil and gas SC.

The purpose of this paper is to explore the scope of applications and benefits of sustainability accounting for the production and industrial use of biomass as an energy source and substitute for fossil‐fuel use. As environmental degradation and unacceptable social impacts not only increase from the production and use of fossil‐fuel based energy, but also from alternative energy sources, the monitoring, controlling and measuring of the (un‐)sustainability of alternative energy production and use emerges as an area in critical need of research.

The paper presents a review of the issues surrounding the accounting for the (un‐)sustainability of industrial biomass production and use, considering what biomass is, the current and forecast importance of industrial biomass, different approaches to its production, and the subsequent measurement and monitoring of its potential (un‐)sustainability.

The paper finds that it is insufficient to conclude in general terms, as is often done or assumed in policy documents and statements, that industrial production and use of biomass is sustainable (or unsustainable) and that accounting for biomass must recognise the broader ecological and social system of which the production and use form a part. A further finding of the paper is that from agricultural or industrial production of biomass through to consumption and industrial use of biomass, the accounting issues surrounding biomass production and use are essential to determining its (un‐)sustainability.

The paper provides an overview of the importance of and problems with the production of biomass for industrial use, and related sustainability issues. It discusses possibilities for and limitations of accounting to address these sustainability issues as well as the need for and the challenges in measuring the (un‐)sustainability of biomass production for industrial use and the accounting for sustainability improvements.

Transport logistics systems in companies with additional public service roles are complex and could benefit from new approaches to performance management. Existing approaches tend to be fragmented; thus, the purpose of this paper is to integrate balanced performance measures, a dynamics model, and the problem-solving method into a new model.

An integrated framework is developed by reviewing literature and synthesising attributes of performance measurement systems, system dynamics and problem-solving methods. The framework is then applied to a multiple-role company’s sea transportation system. The study uses statistical methods to identify performance indicators, management interviews with document study to develop a dynamics model, and simulation methods to formulate an improvement plan.

The performance measurement design stage allowed for the identification of balanced, aligned performance indicators, while the system dynamics model illuminated the impact of the system components’ interrelationships on performance output. The problem-solving method allowed for analysis of system performance, identification of constraints and formulation of a performance improvement plan.

This framework can help transport logistics system stakeholders in multiple-role companies avoid silo thinking, misaligned performance objectives, local optima and short-term solutions.

This study contributes to the existing body of research by introducing a novel framework integrating performance measurement, system dynamics and the problem-solving method. It also addresses a theoretical gap by showing how interconnecting components of sea transportation systems affect transport logistics performance.