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To illustrate the use of a Value Adding Toolbox by construction industry designers when addressing customer value expectations using problem solving.

Focused literature review establishes the need for construction industry design solutions to deliver customer value and a Value Adding Toolbox is proposed in response. Case studies validate Toolbox use and one illustrative example is provided. Interviews with prospective Toolbox users identify barriers to adoption and inform a recommended approach to organisational adoption.

The Toolbox is found to be effective at helping construction designers to solve technical design problems with regard to customer expectations of value. However, designers are found to be initially reluctant to adopt the new tool. Organisation learning is therefore required to establish the importance of customer value satisfaction as a prerequisite to Toolbox adoption by designers.

This paper provides a useful insight into the practical application of problem‐solving tools by construction designers to better understand customer needs.

There are common problems in the identification of uncertain nonlinear systems, nonparametric approximation, state estimation, and automatic control. Dynamic neural network (DNN) approximation can simplify the development of all the aforementioned problems in either continuous or discrete systems. A DNN is represented by a system of differential or recurrent equations defined in the space of vector activation functions with weights and offsets that are functionally associated with the input data.

This study describes the version of the toolbox, that can be used to identify the dynamics of the black box and restore the laws underlying the system using known inputs and outputs. Depending on the completeness of the information, the toolbox allows users to change the DNN structure to suit specific tasks.

The toolbox consists of three main components: user layer, network manager, and network instance. The user layer provides high-level control and monitoring of system performance. The network manager serves as an intermediary between the user layer and the network instance, and allows the user layer to start and stop learning, providing an interface to indirectly access the internal data of the DNN.

Control capability is limited to adjusting a small number of numerical parameters and selecting functional parameters from a predefined list.

The key feature of the toolbox is the possibility of developing an algorithmic semi-automatic selection of activation function parameters based on optimization problem solutions.

This paper aims to examine the development and piloting of a novel European framework for community engagement (CE) in higher education, which has been purposefully designed to progress the CE agenda in a European context.

The proposed framework was co-created through the European Union (EU)-funded project towards a European framework for community engagement in higher education (TEFCE). The TEFCE Toolbox is an institutional self-reflection framework that centres on seven thematic dimensions of CE. This paper follows the development of the TEFCE Toolbox through empirical case study analysis of four European universities and their local communities.

The findings in this paper indicate that the TEFCE Toolbox facilitates context-specific applications in different types of universities and socioeconomic environments. Incorporating insights from engagement practitioners, students and community representatives the TEFCE Toolbox was successfully applied in universities with diverse profiles and missions. The process facilitated the recognition of CE achievements and the identification of potential areas for improvement.

Despite a range of international initiatives, there remains an absence of initiatives within the European higher education area that focus on developing tools to comprehensively support CE. The TEFCE Toolbox and case-study analysis presented in this paper address this gap in knowledge. The broader societal contribution and social responsibility of higher education have become increasingly prominent on the European agenda. The TEFCE Toolbox represents an innovative, robust and holistic European framework with the potential to support universities in reflecting upon their pursuit of addressing grand societal challenges, whilst promoting CE.

Motivated by Morgan’s (1997) analysis of the “paradoxical” role of metaphors in understanding and managing organisations, the purpose of this paper is to assess in what respects organisations using integrated reporting (IR) are on a “journey” of organisational change.

The paper analyses IR practitioner literature to interpret the IR journey metaphor more precisely. The authors then use in-depth interviews to assess the extent to which this metaphor captures how six early adopter organisations in Australia implement IR, and what changes result, over four years.

The journey metaphor implies substantive and holistic organisational change. By contrast, the authors find organisations use IR in contextual, instrumental and piecemeal ways. The authors propose a “toolbox” metaphor to help (re)present how organisations adapt their reporting to fit decisions already made, and challenges presented, through ordinary and ongoing strategic management.

Morgan (1997) stresses metaphors are invariably used to both describe and manage organisations. The authors’ analysis identifies specific ways the IR journey metaphor is descriptively misleading. The authors’ “toolbox” metaphor suggests different ways organisations are, or could, manage IR to create value.

This is the first paper to provide a systematic analysis of the IR journey metaphors, and to assess in what respects this metaphor captures actual organisational practice. The findings also challenge the broader notion in academic research that reporting frameworks can lead organisational change.

The purpose of this paper is to systematically review the relationship and networking strategy tools in the IMP literature. It proposes six dimensions for characterizing such tools: approach to tool development, level (and layer) of analysis, perspective of interaction, activities of network strategizing, external or internal orientation and use for “strategizing on” vs “strategizing in” relationships and networks.

The paper uses a manual qualitative content analysis approach and an inductive approach, well suited for extracting relationship and networking strategy tools due to their implicit and dispersed nature.

The paper presents an IMP toolbox comprising a wide variety of relationship and networking strategy tools emphasizing interconnectedness, interdependence and limited managerial autonomy, as well as an analysis of how identified tools are positioned along each of the six proposed dimensions.

This paper contributes a conceptual framework with a vocabulary to content analyze and discuss relationship and networking strategy tools in IMP research.

The IMP toolbox may be a useful point of departure for managers who feel a need for developing and using a mix of tools for strategizing in business relationships and networks.

The paper instills a strategy tool lens in the IMP literature and foregrounds strategizing concepts and techniques that were previously difficult to attend to for both researchers and practitioners.

Create and share a MATLAB library that performs data augmentation algorithms for audio data. This study aims to help machine learning researchers to improve their models using the algorithms proposed by the authors.

The authors structured our library into methods to augment raw audio data and spectrograms. In the paper, the authors describe the structure of the library and give a brief explanation of how every function works. The authors then perform experiments to show that the library is effective.

The authors prove that the library is efficient using a competitive dataset. The authors try multiple data augmentation approaches proposed by them and show that they improve the performance.

A MATLAB library specifically designed for data augmentation was not available before. The authors are the first to provide an efficient and parallel implementation of a large number of algorithms.

The purpose of this paper is to promote decision-making structures between the customer and the supplier in a highly uncertain environment. This phenomenon of demand-supply chain synchronisation includes sharing of high-quality and timely demand and supply information in order to improve the quality and speed of decision-making.

The study was carried out as an abductive case study, which started from empirical observations that did not match the prior theoretical framework. Through abductive reasoning and empirical experiments, the prior framework was extended to a new synchronisation model and tools that better accommodate the observed need.

A new co-innovation toolbox was developed to create common understanding of demand-supply chain synchronisation between the customer and the supplier. The toolbox includes Demand Visibility Point-Demand Penetration Point, Supply Visibility Point–Supply Penetration Point and Integrative Synchronisation tools.

The study extends the current models and tools of demand-supply chain synchronisation. With the new toolbox, the development needs of decision-making structures can be identified more comprehensively than with the current tools.

The developed visual toolbox helps partners create a common understanding of problems and development possibilities in demand-supply chain synchronisation in a highly uncertain environment. Common understanding is a starting point for changing decision-making structures to improve the overall performance of a demand-supply chain.

The new toolbox is both more comprehensive and more detailed than the previous tools.

Identifying the state of alignment, when there is misalignment, and the path to achieve alignment are of central importance to decision makers today. This paper seeks to offer decision makers some actionable guidance in narrowing the search for possible solution methodologies and to develop a generalized decision alignment framework that can be applied to real decision problems.

Alignment is viewed as a goal of decision makers and the correct matching of decision and action is essential to achieving consistently high performance. Drawing on parallels with the duality problem in linear programming, decision alignment is defined. The decision alignment framework is theoretically developed using examples from a diverse application set, including quantitative research, decision making, education, and e‐commerce.

The evidence shows that good research conforms to the decision alignment framework and poor research violates it. Similarly, good decisions conform to the decision alignment framework and poor decisions violate it. The decision alignment framework guides decision makers in constraining and redefining problems to optimize outcome performance, and shows the importance of addressing the dual problem of learning and understanding the phenomena.

The theoretical foundation developed can be used to promote future research in decision alignment. By providing a theoretically derived framework, rich opportunities for empirical testing are offered. Researchers are also given guidance on how alignment research can be conducted.

The examples presented highlight the prescriptive, communicative, and descriptive value of the decision alignment framework. Practitioners are provided with examples for using the decision alignment framework to build toolboxes of approaches that can be aligned to a characterization of real‐world decision problems to improve performance.

The introduction of a decision alignment framework is a significant contribution to the management decision literature. By introducing a decision alignment framework, the rather ambiguous term alignment is precisely defined as the matching of decision problem characterization (primal problem) with the approach possibility set (dual problem).