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This conceptual paper aims to present a perspective on how to engineer sustainability through the prism of Industry 4.0 technologies and outline propositions to guide future research.

This study presents a literature review developing four research propositions, focusing on the nine leading technologies underpinning Industry 4.0 to engineer economic, environmental and social sustainability dimensions.

The authors derive benefits and challenges of Industry 4.0 technologies across all three business model elements: value creation, value delivery and value capture. The authors derive those for the economic, environmental and social dimensions of sustainability. Thereupon, we develop several propositions for future research.

The authors provide suggestions to practice how to better achieve value in all three sustainability dimensions through implementing a business model perspective, ecosystem thinking, societal demands and Data Governance and AI integration.

By linking societal aspects of Industry 4.0 technologies with environmental, and economic aspects, the authors provide several suggestions how to implement Industry 4.0. For instance, policymakers are recommended to support entire ecosystems than isolated solutions.

The paper contributes to extant literature by conceptualising how Industry 4.0 can leverage value in reaching sustainability in all three dimensions and produce broader ecosystems-wide impacts.

In the practice of live streaming e-commerce, the consumer demand is usually uncertain, and the inventory and prices can be decided by brand owners or streamers. To this end, this study examines the inventory and pricing decisions of the brand owner and streamer in a live streaming e-commerce supply chain under demand uncertainty.

In this study, four scenarios are considered, i.e. the brand owner determines the inventory and price (Scenario BB), the brand owner determines the inventory and the streamer determines the price (Scenario BS), the streamer determines the inventory and the brand owner determines the price (Scenario SB), and the streamer determines the inventory and price (Scenario SS).

The results show that the inventory and prices, as well as the profits of the brand owner and streamer increase with the consumer sensitivity to streamer’s sales effort level under the four scenarios. The inventory (price) is the highest under Scenario SS (SB), while that is the lowest under Scenario BB (BS). In addition, when the sensitivity is low, the brand owner’s profit is the highest under Scenario BB, otherwise, the profit is the highest under Scenario SS. Regardless of the sensitivity, the streamer’s profit is always the highest under Scenario SS.

Few studies focused on the inventory and pricing decisions of brand owners and streamers in live streaming e-commerce supply chains under demand uncertainty, while this work bridges the research gap. This study can provide theoretical basis and decision support for brand owners and streamers.

This study aims to analyse international publications about the Sustainability Balanced Scorecard (SBSC) and the need to integrate Sustainable Development Goals (SDGs) into a Balanced Scorecard (BSC), identifying trends in evolution and future research opportunities.

Based on bibliometric techniques, the outputs obtained in the Web of Science (n = 65) and Scopus (n = 80) databases were analysed in the bibliometrix R package to map and systematically review the literature. After removing duplicates, this paper obtained a final output of 96 articles.

The interconnection between SDGs and BSC is a pertinent and emerging topic in academic and business circles. Therefore, there has been a growing number of publications on SBSC in recent years, particularly in countries such as Qatar, Taiwan, Portugal, Australia, Malaysia and Indonesia. Researchers in these countries have analysed the SBSC, Corporate Sustainability, Corporate Social Sustainability and Performance Evaluation as their main research themes. This research identifies four main research clusters: Strategy and Performance, Model Management Indicators, Balanced Scorecard Decision-Making and, finally, SBSC.

This study contributes to the literature on Sustainability, BSC and SDGs. It can be useful for researchers and organizations that intend to integrate SDGs into a BSC and design an SBSC.

Quality 4.0 is being presented as the new stage of quality development. However, its overlying concept and rationale are still hard to define. To better understand what different authors and studies advocate being Quality 4.0, a systematic literature review was undertaken on the topic. This paper presents the results of such review, providing some avenues for further research on quality management.

The documents for the systematic literature review have been searched on the Scopus database, using the search equation: [TITLE-ABS-KEY (“Quality 4.0”) OR TITLE-ABS-KEY (Quality Management” AND (“Industry 4.0” OR “Fourth Industr*” OR i4.0))]. Documents were filtered by language and by type. Of the 367 documents identified, 146 were submitted to exploratory content analysis.

The analyzed documents essentially provide theoretical discussions on what Quality 4.0 is or should be. Five categories have emerged from the content analysis undertaken: Industry 4.0 and the Rise of a New Approach to Quality; Motivations, Readiness Factors and Barriers to a Quality 4.0 Approach; Digital Quality Management Systems; Combination of Quality Tools and Lean Methodologies and Quality 4.0 Professionals.

It was hard to find studies reporting how quality is actually being managed in organizations that already operate in the Industry 4.0 paradigm. Answers could not be found to questions regarding actual practices, methodologies and tools being used in Quality 4.0 approaches. However, the research undertaken allowed to identify in the literature different ways of conceptualizing and analyzing Quality 4.0, opening up avenues for further research on quality management in the Industry 4.0 era.

This paper offers a broad look at how quality management is changing in response to the affirmation of the Industry 4.0 paradigm.

Credit is essential in the farm business because it facilitates the adoption of productive technologies such as irrigation. However, access to credit remains a significant hurdle for sub-Saharan Africa, including Ghanaian farmers. Therefore, the authors assessed credit utilization and the intensity of borrowing by irrigated rice farmers in the Upper East region. In addition, how extension moderates the amount borrowed was analysed.

The multistage sampling approach was used in the study. The Tono and Vea irrigation schemes were purposively selected. Proportionally, 318 rice farmers were sampled from the Tono irrigation scheme and 159 from the Vea irrigation scheme. Cragg's double hurdle and moderation analysis were used.

It was uncovered that gender, age, years of farming, total farm size, rice farm size, contract farming and off-farm employment explain farmers' decision to borrow. On the other hand, the intensity of borrowing was influenced by gender, age, years of farming, rice farm size, contract farming and the number of extension contact. The moderation analysis revealed that extension contact improves the amount borrowed by farmers.

While there are irrigated rice farmers in other regions of Ghana, this study was limited to rice farmers under the Tono and Vea Irrigation schemes in the Upper East region.

This study investigated the moderating role of extension contact on amount borrowed in Ghana. This makes a modest addition to the limited literature on the moderating role of extension and credit access.

The COVID-19 outbreak has severely impacted the health tourism industry. This study aims to examine the research undertaken on health tourism during COVID-19.

A bibliometric analysis was performed using 211 documents written by 645 authors between 2020 and 2024. The databases used for this analysis are SCOPUS, Web of Science and PubMed. The study was conducted using the Biblioshiny application for R software. Various analyses, including citation analysis, keyword analysis, thematic mapping and evolution and collaboration analysis, were conducted to get a comprehensive picture of the impact of COVID-19 on health tourism.

The findings suggest that medical tourism was the major area of focus for researchers during COVID-19, whereas wellness tourism was studied in the later stages of the pandemic and is considered important for coping with the negative effects of COVID-19. The thematic review indicates that pre-pandemic research focused on strategies that accelerate the growth of the health tourism sector, whereas during and post-pandemic, the focus was on studying the impact of COVID-19 on the survival and recovery of the sector. Overall, health tourism was considered instrumental in the post-pandemic revival of the tourism industry.

The bibliometric analysis is limited to only four years, as the focus was on studying health tourism during COVID-19. Hence, the study offers more precise insights into the research focus on health tourism during a pandemic. The current study offers limited insights into the post-pandemic scenario as the research is still emerging.

There is a significant opportunity for future research on post-COVID-19 recovery strategies, wherein this research will be helpful for researchers, particularly from emerging countries and countries with high dependence on health, medical and wellness tourism. The thematic analysis provides a valuable comparison of pre-, during and post-pandemic research.

The research indicates an opportunity to study the policies and strategies adopted by various countries regarding the health tourism sector in the post-COVID-19 era. The research also highlights the interwoven, intricate, interdisciplinary nature of health tourism in relation to public and mental health and the need for collaborative efforts.

The study provides critical insights and new directions for future research by highlighting the crucial role of health tourism in mitigating the impact of COVID-19.

The purpose of this paper was to document the success and failures of applying Social Cognitive Theory to increase breakfast consumption in a military setting. Breakfast is the most important meal of the day, delivering performance and health benefits. Increasing rates of breakfast consumption may be improved through the application of theory.

Ready to Go, a theory-informed intervention, was piloted in 2022 in one army base in Australia. Ready to Go aimed to embed nine social cognitive theory (SCT) constructs within the pilot programme. Nine SCT indicators were tested using a pre–post design to test whether the theory could be applied to understand potential drivers of behavioural change. A total of 79 participants completed the pre-survey and 74 participants completed the post-survey.

Statistically significant differences were observed for one SCT construct, namely, knowledge, with 10 out of 24 knowledge items improving during the pilot intervention and an increase in rates of breakfast eating on Wednesdays at home was observed. Rates of breakfast eating increased by 13% (from 68% prior to Ready to Go compared to 81% afterwards). Programme participants were satisfied with the programme and reported receiving benefits from programme participation.

Programme data indicates that breakfast eating rates increased and knowledge about healthy eating improved. This paper documents the successes and failures of applying SCT to a pilot programme that aimed to increase breakfast eating rates. This study raises more questions than answers, providing a rich avenue for future research that aims to improve theory application.

The programme used SCT. As far as the authors know, this application of a full reciprocal triad model for breakfast frequency within an institutional setting is novel. Although the theory showed promise for increasing breakfast frequency, adaptation and refinement of the measures may be required for this context to provide more accurate and applicable measurement.

Medicine distribution logistics pattern in pharmaceutical supply chains is a hot topic, which aims to predict applicable and efficient medicine distribution patterns so that the medicine can be distributed effectively. This research aims to propose a new method, named density-distance method, that works based on Kth proximity using patient features (including age, gender, education, inherent diseases, systemic diseases and disorders); geographical features (city, state, population, density, land area) and supply chain features (destination and transportation system).

The proposed method of this research consists of two main phases where in the first phase, quantitative data analytics will be carried out to find out the significant factors and their impacts on medicine distribution. Then, in the next phase, a new Kth-proximity density-distance-based method is proposed to determine the best locations for the wholesalers while designing a supply chain.

The findings show that the proposed method can effectively design a supply chain network using realistic features. In addition, it is found that while the distance-density aggregate index is applied, the wholesalers' locations will be different compared to classic supply chain designs. The results show that age, public hygiene level and density are the most influential during designing new supply chains.

The outcomes of this research can be used in the medicine supply chains to predict appropriate medicine distribution logistics patterns.

In this research, the machine learning method based on the nearest neighbor has been used for the first time in the design of the supply chain network.