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This study aims to investigate the factors influencing the citrus trade in Indonesia, the effects of tariff and non-tariff policies on the industry and the welfare of producers and consumers.

The research used annual series data from 1991 to 2021 and employed inferential, simulation, and descriptive analyses. The two-stage least squares (2SLS) of 19 simultaneous equations were used to estimate parameters.

The results indicate that free trade policies and restrictions have influenced the citrus industry, leading to a reduction in Indonesian citrus imports, and increased consumer and producer prices. However, eliminating import tariff policies on citrus from China and import restrictions increased producer surplus while decreasing consumer surplus, government revenue, and total welfare. Therefore, trade policies should be combined with non-trade policies such as citrus region development policies and advancing cultivation technology.

This study provides empirical evidence for the Indonesian government to formulate effective citrus trade and development policies. It emphasizes the importance of carefully considering the impact of trade policy on the citrus industry and the need to implement non-trade policies such as citrus zone development policies and advancing cultivation technology to benefit both producers and consumers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0148

This study aims to investigate how configurations of boundary objects (BOs) support innovation teams in developing innovative product concepts. Specifically, it explores the effectiveness of different artefact configurations in facilitating collaboration and bridging knowledge boundaries during the concept development process.

The research is based on data from ten undergraduate innovation teams working with an industry partner in a creative industry. Six categories of BOs are identified, which serve as tools for collaboration. The study applies fsQCA (fuzzy-set qualitative comparative analysis) to analyse the configurations employed by the teams to bridge knowledge boundaries and support the development of innovative product concepts.

The findings of the study reveal two distinct groups of configurations: product envisioning and product design. The configurations within the “product envisioning” group support the activities of visioning and pivoting, enabling teams to innovate the product concept by altering the product vision. On the other hand, the configurations within the “product design” group facilitate experimenting, modelling and prototyping, allowing teams to design the attributes of the innovative product concept while maintaining the product vision.

This research contributes to the field of innovation by providing insights into the role of BOs and their configurations in supporting innovation teams during concept development. The results suggest that configurations of “product envisioning” support bridging semantic knowledge boundaries, while configurations within “product design” bridge pragmatic knowledge boundaries. This understanding contributes to the broader field of knowledge integration and innovation in design contexts.

Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.

This study explores the significance and implementation priorities for Digital Product Passports (DPP) in the context of building renovation projects. It aims to reveal bottlenecks and how a data-driven workflow bridges the DPP understanding/implementation gap, facilitating the transition towards practices aligned with the EU Green Deal goals.

A mixed-methods embedded design was employed for a real-case study exploration. Desk research and field observations ground the two-level analysis combining project documentation, namely the Bill of Quantities (BoQ), with different criteria in digitalisation and sustainability, such as economic ratio, 3D modelling, waste management, hazards, energy performance and facility management. All results were interpreted from the DPP lens.

The analysis revealed a system for identifying building products representing a significant part of the renovation budget. About 11 priority DPPs were found. Some are crucial for both the deconstruction and construction phases, highlighting the need for an incremental and strategic approach to DPP implementation.

The study is limited to a single case study. Constraints are minimised given the sample's archetype representativeness. The outcomes introduce the need for strategic thinking for incremental DPP implementation. Future research will explore additional criteria and cases.

The research has resulted in a classification framework for DPPs' significance and priority, which is provided with case results. The outcome of the framework provides views on concept alignment to make the implementation in construction more straightforward. Its practical use can be replicated in other projects, emphasizing the importance of data structure and management for the circular economy.

As sustainable performance has a central role in the small and medium enterprises (SMEs) performance literature, this study aims to examine the influence of networking capabilities in enhancing sustainable performance through knowledge workers’ productivity and digital innovation. It also examines the sequential mediating role of knowledge workers’ productivity and digital innovation on networking capabilities and SMEs’ sustainable performance relationship.

Data were collected from 308 knowledge workers in the information technology sector and analyzed using the Hayes Process Macro bootstrapping method to test the proposed hypotheses.

Results indicate that knowledge workers’ productivity and digital innovation individually and sequentially mediate the relationship between networking capabilities and SME’s sustainable (economic and environmental) performance, surprisingly, they do not act as a mediator between networking capability and SME’s social performance. SMEs should prioritize investments in the professional development of their knowledge workers through training and skill enhancement programs. This investment equips knowledge workers with the tools to effectively use the knowledge and resources acquired through networking. Thus, knowledge workers may improve performance by using these resources to tackle challenges.

Although this research focused on this specific context, it is prudent to acknowledge that additional factors may also exert influence on sustainable performance within SMEs, factors that managers may consider when making decisions. Methodologically, the cross-sectional design of this research poses a potential limitation, as it does not allow for the complete elimination of endogeneity concerns. However, it is worth noting that scholars have endorsed the use of cross-sectional data in cases where management researchers aim to expand beyond well-documented and longitudinal data sets.

This research offers practical recommendations for SMEs to improve their sustainable performance through networking. SMEs should seek partnerships with complementary knowledge to improve operations and for other performance-oriented benefits.

This study adds significantly to the literature on sustainable SME performance by studying the interdependent effects of networking capabilities. It also represents the individual and sequential mediation mechanism that links networking capabilities to SME success through knowledge worker productivity and digital innovation.

This chapter examines the explosion in International Humanitarian Law between the US Civil War and World War I. The primary foci are the Hague Conventions on land warfare and the Geneva Conventions for the sick and wounded. This body of treaties is the foundation of IHL and the modern laws of war. Most of central issues in the international laws of war emerge in this period.

Higher education institutions and their lecturers are strategic agents and main drivers that contribute to circular economy transition. This requires them to understand the key circular economy competencies and how to integrate circular economy holistically into their curricula with the suitable teaching and learning approaches. This study aims to support them by providing an overview on the characteristics of education for the circular economy (ECE) and suggestions to lecturers to further develop their curricula.

The data consisted of scientific articles (n = 22) describing circular economy courses in higher education. Qualitative content analysis with quantitative features was performed on the selected articles to answer the research question.

The findings confirm that the system’s focus is the key issue in ECE. However, to integrate circular economy holistically into the curricula, ECE should be implemented more widely in the context of different industries and market contexts to find innovative teaching and learning approaches. The demand side needs to be incorporated in the courses, as systemic transformation is also about transforming consumption. All levels of implementation and circular economy objectives should be included in courses to promote systems thinking. In addition, innovative forms of real workplace interaction should be increased.

As ECE has started to emerge as a new field of study, this article provides the first integrated overview of the topic.

This study evaluates how well Victorian local councils’ procurement policies align with the sustainable and circular economy (CE) approach that prioritises sustainable and regenerative practices. It proposes a set of criteria designed to effectively integrate environmental sustainability issues into purchasing policies.

Employing the Specific, Measurable, Assignable, Realistic and Time-bound (SMART) framework, a multi-dimensional content analysis guided by the goal-setting theory was applied to evaluate all 79 Victorian local councils’ procurement policies. This approach provided an assessment of policy specificity, measurability, assignability, realism and time sensitivity in promoting environmental sustainability through purchasing policies.

The findings underscored a significant deficiency in policy adherence to all SMART criteria concerning environmental sustainability, hindering the effective green purchasing decisions within government entities. This lack of integration of greening in purchasing policy poses challenges for manufacturers of waste-derived goods, obscuring the procurement objectives of these critical public sector customers.

The paper contributes to the sustainable procurement (SP) discourse by proposing guidelines aimed at improving the efficacy of governmental purchasing of sustainable products. These guidelines address the broader imperative to mitigate the environmental impacts of governmental spending on less sustainable goods, thereby fostering ecological sustainability and promoting responsible consumption.

While past studies have often relied on subjective content analysis methods, the SMART assessment used to develop the environmental sustainability criteria for purchasing policies, which distinguishes this study from previous governmental policy evaluation studies. This approach marks a departure from traditional governmental policy evaluation studies, offering a more structured analysis of policy effectiveness in promoting SP practices.

Today’s businesses are looking for a circular bioeconomy (CBE) to develop a sustainable manufacturing process as industrial operations result in significant amounts of waste materials and the depletion of natural sources. The industry commonly applies techniques such as lean manufacturing (LM), digital innovations (DI) and green practices (GP) for operational and quality improvement. However, publications explaining how these technologies enable the CBE transition are scarce. This study examines CBE components, common practices of each technology facilitating the CBE transition, problems of solitary technology deployment as well as coupling technologies for the CBE transition.

A scoping review was conducted to analyse previous studies in this new field. The data collection is in a quantitative manner, but the data synthesis process follows a similar method of synthesising data in the grounded theory method, which includes familiarisation with the data, open-coding and finalisation of the themes.

Critical components of CBE were identified as biobased goods, industry symbiosis, material resource efficiency, renewable energy, product lifecycle and sharing economy. GP is the most prominent in moderating the CBE transition. We identify each technology has coupled relationships (Lean-4.0, Green-Lean and Green-4.0) technologies facilitated by the circularity concept, which form the core pillars of enablers and advance the CBE paradigm.

This study demonstrates that combining lean principles with green technology and digital technologies can effectively decrease waste and resource usage in biobased manufacturing processes, therefore endorsing the concept of resource efficiency in circular bioeconomy models.

The results allow entrepreneurs to strategically incorporate different existing technologies to meet CBE fundamental objectives by initiating it with dual technologies and facilitate industry professionals and regulators to support the improvement of environmental sustainability performance in the manufacturing industry. The management will be able to focus on the common practices across the technologies, which have a dual benefit for both operational and environmental performance.

The paper makes the first attempt to present the synergic impact of the three quality management technologies on a new concept of sustainability, CBE.

The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training in the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.

This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry.

The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.

Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.