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This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

While digital transformation holds immense promise, organizations often fail to realize its benefits. This study aims to address how policies for digital transformation benefits realization are translated into practice.

The authors apply a qualitative, comparative case study of two large, public-sector health care organizations in Sweden. Through document and interview data, the authors analyze the process of translation.

The study finds that practice variation is primarily caused by two types of decoupling: policy-practice and means-ends. Contrary to previous studies, coercion in policy compliance is not found to decrease practice variation.

The limitations primarily stem from the empirical selection of two large public health-care organizations in Sweden, affecting the study’s generalizability. Reducing practice variation is more effectively achieved through goal alignment than coercion, leading to implications for the design of governance and control.

Policymakers should, instead of focusing on control-related compliance, work to align organizational objectives and policies to decrease practice variation for successful benefits realization.

The study contributes to better benefits realization of digital transformation initiatives in health care. As such, the authors contribute to a better functioning and more transformative health care in times of increased demand and decreased supply of health-care services.

The study challenges conventional wisdom by identifying that coercion is less effective than goal alignment in reducing practice variation, thereby enhancing the understanding of policy implementation dynamics in health-care settings.

This study aims to examine the impact of national culture on classification shifting in Eastern European Member States of EU Eastern European countries (EEU) vis-à-vis the Western Member States of EU (WEU). The EEU provides a unique sample to study the quality of financial reporting that the authors measure with classification shifting given that for more than five decades they were following the model of a centrally planned economy, where market-based financial reporting was absent. Yet, the EEU transitioned to a market-based economy and completed its accession to the EU.

This study uses a panel data set of firm year observations from 1996 and 2020 that covers the full transition of EEU. This empirical analysis is based on fixed effects panel regression analysis where the authors report a plethora of identifications.

This study finds classification shifting in the EEU countries since their transition to the market-based economy, though they have no long record of market-based financial reporting. This study also notices that cultural factors are associated with classification shifting across all Member States of the EU. This study further examines the impact of interactions between cultural characteristics and special items and reveal variability between WEU and EEU. As part of the robustness analysis, this study also tests the impact of culture on real earnings management measures for both WEU vs EEU, confirming the variability of the impact of culture on earnings management.

Future research could explore the role of religion differences in WEU vis-à-vis EEU states, as they are also subject to cultural differences.

The findings are important for regulators, external monitors and investors, as they show that cultural factors affect earnings management with some variability across countries in the EU, and they should be acknowledged in policymaking.

The findings show that cultural differences between EEU and the “old” Member States of the EU could explain classification shifting.

To the best of the authors’ knowledge, this is the first study that sheds light on the impact of national culture on classification shifting in EEU of EU vis-à-vis the “old” WEU of EU.

This study aims to develop a conceptual framework for the role of chief financial officer (CFO) in an ever-changing environment. As previous research focused on responding to specific crises, there have been theoretical and practical gaps in the role of CFO. The study's goal is to fill a critical gap by developing a comprehensive and integrated set of roles to assist the CFO in a constantly changing environment.

Using a grounded theory approach, semi-structured interviews and observations were conducted with 21 CFOs from various industries in Thailand, including foreign multinational corporations and domestic companies with international operations. CFOs were asked how they frame their roles in the face of an ever-changing environment and how they prepare for the future.

The iCFO model is developed, which identifies the critical “core” roles of the CFO in securing the business foundation, as well as the “future opportunities” roles that function as growth engines for long-term business strength. The research delves into the importance of integrity, ethical mindset and corporate governance in the role of the CFO. The iCFO model is designed to help guide future research and provide practical applications for CFOs in both domestic and international contexts. The term “core” refers to the CFO’s primary responsibilities, which include driving profitability, managing risks and optimizing business performance. The “future opportunities” component focuses on the roles that CFOs can play in strengthening the future of business by optimizing investment efficiency, driving digital transformation and being the CEO’s business partner. The findings also emphasized “integrity,” which must encompass all decisions, actions or recommendations made by the CFO.

The study offers unique perspectives on an emerging economy, providing new insights. Through interviews with 21 CFOs, it contributes empirical evidence on the development of roles in accounting and finance, emphasizing good governance practices. The findings highlight the integrated role of the CFO and their self-reflection on their value within the company. Significantly, the study's implications are relevant and applicable to a global audience, particularly in developing economies that prioritize growth. Future studies could incorporate integrated thinking into the iCFO model to address social, environmental and economic factors, making it more universally relevant. Additionally, exploring the adoption of the chief value officer context in developing markets could enable CFOs to expand their focus beyond financial metrics, embracing a comprehensive approach to value creation. By integrating these concepts into the iCFO model, CFOs can effectively drive sustainable and impactful business outcomes on a global scale.

This study aims to present the variations of optimal seismic control of reinforced cement concrete (RCC) structure using different structural systems. Different third-dimensional mathematical models are used to examine the responses of multistory flexibly connected frames subjected to earthquake excitations.

This paper examined a G + 50 multi-storied high-rise structure, which is analyzed using different combinations of moment resistant frames, shear walls, seismic outrigger systems and seismic dampers to observe the effectiveness during ground motion against soft soil conditions. The damping coefficients of added dampers, providing both upper and lower levels are taken into consideration. A finite element modeling and analysis is generated. Then the nature of the structure exposed to ground motion is captured with response spectrum analysis, using BNBC-2020 for four different seismic zones in Bangladesh.

The response of the structure is investigated according to the amplitude of the displacements, drifts, base shear, stiffness and torsion. The numerical results indicate that adding dampers at the base level can be the most effective against seismic control. However, placing an outrigger bracing system at the middle and top end with shear wall can be the most effective for controlling displacements and drifts.

The response of high-rise structures to seismic forces in Bangladesh’s soft soil conditions is examined at various levels in this study. This study is an original research which contributes to the knowledge to build earthquake resisting high-rises in Bangladesh.

This study aims to assess the facilities management (FM) strategies used in multi-tenanted purpose-built office buildings (Mt-POBs) in Ghana and the drivers that influence the decision to use such strategies.

This study was conducted via a survey and key informant interviews. The survey was conducted using a questionnaire targeted at 65 multi-tenanted office building owners in the Greater Accra region. The data from the survey revealed the views of building owners on FM strategy and the extent to which 20 facility management decision drivers influenced their decisions to use a particular strategy and the responses were descriptively analysed. The key informant interviews were conducted among six leaders of the property owners’ association who use in-house FM to further understand their perspectives and decisions on using such strategy. The interviews were conducted over telephone using an interview guide and analysed using thematic analysis.

The results showed that 88% of Mt-POBs in Ghana are managed in-house. The results also showed that the decision to use the in-house strategy was driven by the innovative, strategic and cost-saving advantages associated with the in-house strategy.

This study shows the factors that drive the decision of multi-tenanted office building owners in Ghana to use the in-house strategy. The findings of this study will be useful for prospective owners of office buildings in Ghana.

This paper offers a definition of the core of information science, which encompasses most research in the field. The definition provides a unique identity for information science and positions it in the disciplinary universe.

After motivating the objective, a definition of the core and an explanation of its key aspects are provided. The definition is related to other definitions of information science before controversial discourse aspects are briefly addressed: discipline vs. field, science vs. humanities, library vs. information science and application vs. theory. Interdisciplinarity as an often-assumed foundation of information science is challenged.

Information science is concerned with how information is manifested across space and time. Information is manifested to facilitate and support the representation, access, documentation and preservation of ideas, activities, or practices, and to enable different types of interactions. Research and professional practice encompass the infrastructures – institutions and technology –and phenomena and practices around manifested information across space and time as its core contribution to the scholarly landscape. Information science collaborates with other disciplines to work on complex information problems that need multi- and interdisciplinary approaches to address them.

The paper argues that new information problems may change the core of the field, but throughout its existence, the discipline has remained quite stable in its central focus, yet proved to be highly adaptive to the tremendous changes in the forms, practices, institutions and technologies around and for manifested information.

Concrete-filled double skin tube (CFDST) columns are considered one of the most effective steel-concrete composite sections owing to the higher load carrying capacity as compared to its counterpart concrete-filled tube (CFT) columns. This paper aims to numerically investigate the performance of axially loaded, circular CFDST short columns, with the innovative strengthening technique of providing stiffeners in outer tubes. Circular steel hollow sections have been adopted for inner as well as outer tubes, while varying the length of rectangular steel stiffeners, fixed inside the outer tubes only, to check the effect of stiffeners in partially and full-length stiffened CFDST columns.

The behaviour of these CFDST columns is investigated numerically by using a verified finite element analysis (FEA) model from the ABAQUS. The behaviour of 20-unstiffened, 80-partially stiffened and 20-full-length stiffened CFDST columns is studied, while varying the strength of steel (f_yo = 250–750 MPa) and concrete (30–90 MPa).

The FEA results are verified by comparing them with the previous test results. FEA study has exhibited that, there is a 7%–25% and 39%–49% increase in peak-loads in partially stiffened and full-length stiffened CFDST columns, respectively, compared to unstiffened CFDST columns.

Enhanced strength has been observed in partially stiffened and full-length stiffened CFDST columns as compared to unstiffened CFDST columns. Also, a significant effect of strength of concrete has not been observed as compared to the strength of steel.

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.