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Wicked problems require collaborative innovation approaches. Understanding the problem from the users' perspective is essential. Based on a complex and ill-defined case, the purpose of the current paper is to identify some critical success factors in defining the “right problem” to be addressed.

An empirical research study was carried out in a low-density municipality (case study). Extensive data were collected from official databases, individual semi-structured interviews and a focus group involving citizens, local authorities, civil servants and other relevant stakeholders.

As defined by the central government, the problem to be addressed by the research team was to identify which justice services should be made available locally to a small- and low-density community. The problem was initially formulated using top-down reasoning. In-depth contact with citizens and key local players revealed that the lack of justice services was not “the issue” for that community. Mobility constraints and the shortage of economic opportunities had a considerable impact on the lack of demand for justice services. By using a bottom-up perspective, it was possible to reframe the problem to be addressed and suggest a new concept to be tested at later stages.

The approach followed called attention to the importance of listening to citizens and local organisations with a profound knowledge of the territory to effectively identify and circumscribe a local problem in the justice field.

The paper highlights the limitations of traditional rational problem-solving approaches and contributes to expanding the voice-of-the-customer principle showing how it can lead to a substantially new definition of the problem to be addressed.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

This empirical study uncovers emotional sensemaking factors that cause changes in management perceptions about wicked strategic problems under dynamic complexity. These perception changes improve understanding of, and solutions to, the wicked problem.

Senior managers from three large organizations in different sectors participated in gaming simulation workshops. The strategic issues at stake were intractable and divisive. Qualitative methods captured participants' perceptions of the problems and the dynamic complexity that they faced and how they changed.

Flawed management perceptions were revised as sensemaking processes were catalyzed by emotions of shock/surprise that came from experiencing unexpected stakeholder conduct within a simulation. The plausibility of the conduct was strengthened because managers were role-playing stakeholders. The shock/surprise emotion uncoupled attachment to entrenched beliefs, leading to a willingness to revise the flawed perceptions. The changed perceptions created new insights for a solution to the wicked problem.

Practical implications are how management practitioners can improve the tackling of wicked strategic problems through the use of shock and surprise in a gaming simulation.

This research extends theory on the role of emotions in sensemaking under dynamic complexity. The authors uncover how a hierarchy of managers' emotions used in sensemaking explains the catalytic effect of the shock and surprise of unexpected stakeholder conduct on revisions to their perceptions of the outcomes of the dynamic complexity.

Path planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.

Firstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.

Simulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.

Aiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.

Selecting and scheduling optimal project portfolio simultaneously is a complex decision-making problem faced by organizations to realize the strategy. However, dynamic synergy relationships among projects complicate this problem. This study aims at constructing a project portfolio selection and scheduling (PPSS) model while quantifying the dynamic synergetic effects to provide decision support for managing PPSS problems.

This study develops a mathematical model for PPSS with the objective of maximal project portfolio benefits (PPBs). To make the results align with the strategy, comprehensive PPBs are divided into financial and non-financial aspects based on the balanced scorecard. Then, synergy benefits evolve dynamically in the time horizon, and system dynamics is employed to quantify them. Lastly, a case example is conducted to verify the applicability of the proposed model.

The proposed model is an applicable model for PPSS while incorporating dynamic synergy. It can help project managers obtain the results that which project should be selected and when it should start while achieving optimal PPBs.

This study complements prior PPSS research in two aspects. First, financial and non-financial PPBs are designed as new criteria for PPSS, making the results follow the strategy. Second, this study illuminates the dynamic characteristic of synergy and quantifies the synergetic effect. The proposed model provides insights into managing a PPSS effectively.

The paper frames modern slavery as a global wicked problem and aims to provide a set of international business (IB) policy recommendations for taming it. The outlined approach can also guide IB policymaking to address other kinds of wicked problems.

This is a conceptual paper that reviews existing literature on wicked problems and integrates it with an IB policy double helix framework. The paper focuseses on the role multinational enterprises (MNEs) play in moderl slavery globally, either through global value chains or within global factory modes of operation.

As a global wicked problem, modern slavery will never be solved, but it can be re-solved time and time over. Understanding the social reproduction of modern slavery can help shift the focus from labor governance and a narrow supply chain focus toward the role of transnational governance and the need to address institutional, market and organizational failures.

The paper contributes to the gap in an overarching theory of modern slavery and systematically applies the concept of wicked problems and wickedness theory to modern slavery. Drawing on an IB policy double helix framework, the paper addresses the governance nexus between modern slavery, IB and policymaking which can in turn advance IB policy research and theory.

Given the importance of interdisciplinary research in addressing wicked problems, this paper aims to explore the development of and prospects for interdisciplinary research through evidence gained from academic accountants in Australia.

Extant literature is complemented with interviews of accounting academics in Australia to reveal the challenges and opportunities facing interdisciplinary researchers and reimagine prospects for the future.

Evidence indicates that accounting academics hold diverse views toward interdisciplinarity. There is also confusion between multidisciplinarity and interdisciplinarity in the journals in which academic accountants publish. Further, there is mixed messaging among Deans, disciplinary leaders and emerging scholars about the importance of interdisciplinary research to, on the one hand, publish track records and, on the other, secure grants from government and industry. Finally, there are differing perceptions about the disciplines to be encouraged or accepted in the cross-fertilisation of ideas.

This paper is novel in gathering first-hand data about the opportunities, challenges and tensions accounting academics face in collaborating with others in interdisciplinary research. It confirms a discouraging pressure for emerging scholars between the academic research outputs required to publish in journals, prepare reports for industry and secure research funding, with little guidance for how these tensions might be managed.

Food sector supply chains have significant negative environmental impacts, including the expansion of global food commodity production, which is driving tropical deforestation – a major climate and biodiversity problem. Innovative supply chain monitoring services promise to address such impacts. Legislation also designates “forest-risk commodities”, demanding supply chain due diligence of their provenance. But such data alone does not produce change. This study investigates how theory in performance measurement and management (PMM) can combine with sustainable supply chain management (SSCM) and decision theory (DT) via case study research that addresses paradoxes of simplicity and complexity.

Given existing relevant theory but the nascent nature of the topic, theory elaboration via abductive case study research is conducted. Data collection involves interviews and participatory design workshops with supply chain actors across two supply chains (coffee and soy), exploring the potential opportunities and challenges of new deforestation monitoring services for food supply chains.

Two archetypal food supply chain structures (short food supply chains with high transparency and direct links between farmer and consumer and complex food supply chains with highly disaggregated and opaque links) provide a dichotomy akin to the known/unknown, structured/unstructured contexts in DT, enabling novel theoretical elaboration of the performance alignment matrix model in PMM, resulting in implications for practice and a future research agenda.

The novel conceptual synthesis of PMM, SSCM and DT highlights the importance of context specificity in developing PMM tools for SSCM and the challenge of achieving the general solutions needed to ensure that PMM, paradoxically, is both flexible to client needs and capable of replicable application to deliver economies of scale. To advance understanding of these paradoxes to develop network-level PMM systems to address deforestation impacts of food supply chains and respond to legislation, a future research agenda is presented.

The purpose of this study is to formulate a new class of vehicle routing problem with an objective to minimise the total cost of raw material collection and derive a new approach to solve optimization problems. This study can help to select the optimum number of suppliers based on cost.

To model the raw material vehicle routing problem, a mixed integer linear programming (MILP) problem is formulated. An interesting phenomenon added to the proposed problem is that there is no compulsion to visit all suppliers. To guarantee the demand of semiconductor industry, all visited suppliers should reach a given raw material capacity requirement. To solve the proposed model, the authors developed a novel hybrid approach that is a combination of block and edge recombination approaches. To avoid bias, the authors compare the results of the proposed methodology with other known approaches, such as genetic algorithms (GAs) and ant colony optimisation (ACO).

The findings indicate that the proposed model can be useful in industries, where multiple suppliers are used. The proposed hybrid approach provides a better sequence of suppliers compared to other heuristic techniques.

The data used in the proposed model is generated based on previous literature. The problem derives from the assumption that semiconductor industries use a variety of raw materials.

This study provides a new model and approach that can help practitioners and policymakers select suppliers based on their logistics costs.

This study provides two important contributions in the context of the supply chain. First, it provides a new variant of the vehicle routing problem in consideration of raw material collection; and second, it provides a new approach to solving optimisation problems.

Through the action research study, this paper aims to examine how e-portfolios improve students’ critical, reflective and creative thinking as part of higher-order thinking skills (HOTS). Besides, this paper also explores how e-portfolios enhance students’ speaking skills. The study is carried out to improve the current state by identifying and solving problems in specific contexts.

This investigation was designed to seek the improvement of the students’ higher-order thinking and speaking skills after the implementation of the e-portfolio. Action research was chosen because action research is suitable to bring change and improvement in the system or assume to bring progress in the system. This study was designed in two phases, featuring reflection and connection between previous and new data.

By completing this action research study, the authors assisted students in improving their higher-order thinking and speaking skills. The improvement was related to the indicators for learning success, which were explained in this research. The HOTS criteria include the capacity to analyze essential facts and arguments that the students presented in their spoken works logically and critically.

HOTS encompasses critical, logical, creative and metacognitive thinking skills. Future research should go further into the usage of e-portfolios in the development of students’ metacognitive capacities. Moreover, because this investigation was carried out using action research methods, it is crucial to recognize that no generalizability can be offered for the findings.

The study’s findings should also benefit practitioners and instructors endeavoring to enhance students’ e-portfolios, critical thinking and digital skills in the classroom.

The discussion focuses on important development topics. Everyone, not just students, should be encouraged to participate in creating and developing our technological future. The analysis offers unique and essential perspectives into what to explore for such a substantial attempt as implementing digital technology, specifically to construct an e-portfolio.

Despite the widespread usage of e-portfolios in English as a foreign language (EFL) instruction, there is a lack of research on how e-portfolios can enhance EFL students’ HOTS and speaking abilities. Hence, this study addresses a deficiency in existing research by examining the potential of e-portfolios to enhance students’ HOTS and oral communication skills within the context of EFL.