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This paper explores how adaptive organizations, companies capable of continuously adapting their organizational model, dynamically solve the universal problems of organizing.

The authors applied grounded theory to data acquired from six interpretative case studies, collected in two rounds of interviews (15 in total), then completing and validating the study’s evidence through triangulation with several secondary data sources.

In adaptive organizations, polyarchies and intrapreneurial employees are essential to shape the division of labour, leading to high levels of autonomy and empowering individuals and teams, while reducing bureaucracy and hierarchy. In terms of the integration of effort, digital solutions are preferred to social proof in the provision of information, while the authors note that incentives are always geared towards developing strong higher-order dynamic capabilities.

This paper has some limitations that could be addressed in future research, including longitudinal studies to analyse the link between the universal problems of organizing and a company's dynamic capabilities.

Adaptive organizations go beyond tech firms in responding to the universal problems of organizing work by making specific use of digital technologies.

The paper studies how companies should organize themselves so that they continuously adapt to an ever-changing competitive environment.

This paper aims to examine the fundamental conditions which are necessary for the construction of a regulation which will affect a genuine advancement in the context of environmental protection.

The component parts of an adequately built regulation are broken down to concretise the notion of efficacy – and its proposed universality – in a regulatory context. This paper takes a comparative approach of regulations and extends to include a consideration of the monitoring and enforcement of regulation as a necessary tenant of an effective regulation.

Sustainability regulations have seen a significant development in the 20th century. Notable remain the national discrepancies to so universal problem, as well as an inconsistent acknowledgement of the purpose of sustainability regulations beyond a tick-box compliance commitment.

The importance of sustainability has been amplified without a due consideration of what its translation into regulation must look like. This paper argues that no meaningful change can be lobbied without understanding how its practical implementation is performed.

Algorithmic and computational thinking are necessary skills for designers in an increasingly digital world. Parametric design, a method to construct designs based on algorithmic logic and rules, has become widely used in architecture practice and incorporated in the curricula of architecture schools. However, there are few studies proposing strategies for teaching parametric design into architecture students, tackling software literacy while promoting the development of algorithmic thinking.

A descriptive study and a prescriptive study are conducted. The descriptive study reviews the literature on parametric design education. The prescriptive study is centered on proposing the incomplete recipe as instructional material and a new approach to teaching parametric design.

The literature on parametric design education has mostly focused on curricular discussions, descriptions of case studies or studio-long approaches; day-to-day instructional methods, however, are rarely discussed. A pedagogical strategy to teach parametric design is introduced: the incomplete recipe. The instructional method proposed provides students with incomplete recipes for parametric scripts that are increasingly pared down as the students become expert users.

The article contributes to the existing literature by proposing the incomplete recipe as a strategy for teaching parametric design. The recipe as a pedagogical tool provides a means for both software skill acquisition and the development of algorithmic thinking.

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 study aims to examine whether or not residential properties closer to landfill sites have lower offer values by the developers. That is, by analyzing real estate data and landfill site locations, the study seeks to provide insights into whether properties situated closer to landfill sites tend to have a lower offer values than those located farther away.

The study is exploratory in nature, and a case study approach is applied. A landfill site named “Uruli Devachi” is selected in the region of Pune district, and data is collected from 102 developers selling residential projects within a radius of 15 km (about 9.32 mi). The gathered data is analyzed by using basic descriptive statistics, one-way ANOVA and ordinary least squares (OLS) regression. The OLS regression helps to determine whether there is a relationship between the distance of a residential property from a landfill site and its offer value.

The findings suggest that landfill sites have a detrimental impact on residential property offer values, with the negative impact increasing with proximity to a landfill site. The negative effect seems to vanish after over 10 km (about 6.21 mi). The developers provide extra facilities including a clubhouse, a children’s play area, a gym and a swimming pool in an effort to mitigate the negative effects of the landfill site on residential properties.

The findings of this study could have implications for property developers, real estate professionals and policymakers in understanding how landfill proximity might impact property offer values.

This study presents many novelties for the Indian housing market: the landfill sites do have a negative effect on the offer value of residential property; the closer the residential property to a landfill site, the higher the negative effect. Further, the developers try and mitigate the negative effect of landfill sites on residential properties by providing additional amenities such as a clubhouse, children’s play park, gym and swimming pool.

The purpose of this study is to propose a model for integrating microgames in teaching primary Education for Sustainable Development (ESD) and illustrate the application of the proposed model in teaching integrated mathematics, arts, technology and language in primary ESD.

The model was based on conceptual mapping from the reviewed literature and reflection from their teaching experience.

The model and the related teaching-learning activities have been proposed.

The proposed model enhances the use of microgames in an interdisciplinary teaching framework.

Successful digital transformation involves all areas which bring new impacts and challenges to the leadership of the enterprise. From the perspective of organizational identification, the authors construct a theoretical model of digital leadership–digital strategic consensus–digital transformation and explore the different moderated mediation effects of diversity types.

This paper obtains data from 351 Chinese science and technology enterprises and uses regression analysis and bootstrap analysis to test the research hypotheses.

The results demonstrate that digital leadership has a positive impact on digital transformation. Digital strategic consensus partially mediates the linkage between digital leadership and digital transformation. Disparity diversity and variety diversity positively moderate the mediating role of digital strategic consensus between digital leadership and digital transformation, respectively; and separation diversity negatively moderates the mediating role of digital strategic consensus between digital leadership and digital transformation.

The research innovatively measures digital leadership and digital transformation. It expands the application of leadership, strategic consensus, diversity and other related theories in a digital context and provides a decision-making basis for enterprises' digital transformation.

In the past few years, researchers across the world have been attracted to corporate governance (CG) and sustainability studies in the banking space. However, inconsistencies remain, which have created a lack of alignment in existing research. To address this problem, this paper aims to re-examines the CG–bank sustainability relationship using a qualitative design, which has been underused in the field, to generate in-depth, useful and novel analysis and insights that may hide behind the numbers.

A qualitative inquiry was conducted using key informants in Ghana’s banking industry. This study made use of purposive and snowball sampling techniques, an interview guide and the thematic approach to qualitative data analysis.

Firstly, this research finds that while larger boards do not promote bank sustainability, those who are independent and have diversified expertise and experiences do. Secondly, CEO duality can boost bank sustainability only if the CEO is actively engaged and performing. Thirdly, this study finds that foreign-owned and managed banks make more profits only if they have good knowledge of the local market.

This research makes the call that upcoming researchers should replicate this research in other banking settings worldwide to validate the results.

Practical lessons for local and foreign-owned banks and their shareholders are discussed to advance the United Nations’ Sustainable Development Goal 8.

This research shares novel insights that offer clarity to the literature and move the CG and sustainability fields forward.

Problem-solving, systems thinking and design thinking are disciplines practiced by all human beings and is also innate in other living objects with limited use of symbolic structures. They are necessary to achieve the goals and survive. Interpretation of problem-solving as a change in equilibrium makes it applicable throughout the inanimate world. The aim is to describe the proposed empirical systems theory that integrates problem-solving and systems thinking through design thinking.

A brief historical background describes why comprehensive empirical systems theory has not been attempted before except as a restricted version in engineering systems. The methodology of the general theory follows that of conventional science, but with systemic content. Interference by required mental or physical product/systems changes states which is subject to discussion, creativity, innovation and inspiration accomplished by iteration as necessary.

A problem-solving structure has been created, which is implemented in a methodical way to aid the innate ability of individuals and organisations, and is open to modifications and the use of quantitative methods. Processed natural language allows for implementation at the operational level.

The proposed systems theory is an empirical theory that uses the structural properties of parts of the world. The integration makes “systems” the driver of change of state and offers fundamental concepts. The implementation shown in Figure 2 is methodical and can be applied by individuals and organisations subject to peer review and development. The method clarifies the roles of product/artifact and systems designers.

The dearth of leadership competencies to transform traditional industries to Industry 4.0 is a barrier to global production. This study explains the deficiencies in leadership competencies that hinder the transformation of traditional industries to Industry 4.0.

Leadership was explained into transactional leadership, digital leadership and Leadership 4.0. Then, the network of relationships between these leadership constructs was plotted in a path diagram to learn the mediating effect of digital leadership.

The results indicate that a lack of digital competencies to coordinate tasks, share information and solve problems in a digitalized environment is the barrier to the transformation.

The findings can be used in human resources (HR) management. In addition, the findings provide evidence to present the contingency theory as a universal theory of leadership.

The study is the first to assess the mediating effect of digital leadership on transactional leadership to explain the changes to strategic leadership due to the emergence of Leadership 4.0.