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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.

The study aims to define the term “generation” by proposing an integrated design based on age-period-cohort effects and by proposing an Indian generational cohort framework categorizing Indian generational cohorts into four categories, namely, Baby Boomers, GenX, GenY, and GenZ. The study further aimed to capture the existing generational differences between GenY and GenZ cohorts in the Indian teams on team climate, transactive memory system, and team leader humility.

For the first two objectives a literature review methodology along with the author's proposition was adopted. An integrated design was proposed by reviewing the relevant sociological literature to define generations. Thereafter, an Indian cohort framework was proposed categorizing them into four groups Baby Boomers, GenX, GenY, and GenZ. Following that, for the last objective, i.e. to identify the differences between cohorts, empirical data were collected by a structured questionnaire that was disseminated to GenY and GenZ Indian working professionals. A total of 229 responses were used for observing the differences or similarities between GenY and GenZ cohorts on the study variables by employing an independent samples t-test.

The study proposed an integrated design (age, period, and cohort effect). Following that, an Indian generational cohort's framework has been outlined categorizing Indian cohorts based on their birth years, age groups, developmental stages, formative years, major Indian historical events, and various characteristics possessed by them. Moreover, the empirical findings support the existing generational disparities and depict that GenZ holds a higher inclination towards transactive memory systems and team climate whereas GenY holds more inclination toward leader humility.

The study put forth its contribution to research scholars by categorizing Indian generational cohorts in a rationalized manner based on an integrated design (age-period-cohort) effect. The study would further assist concerned authorities and managers in formulating HR policies to deal with the underlying generational differences highlighted by the study.

As there lies a paucity of generational frameworks in the Indian context, this study is the first attempt in this direction which categorizes Indian generational cohorts based on a unique integrated design including age-period-cohort effects. In addition, the study also investigated these cohorts in Indian organizations to observe the existing variations.

The accurate prediction of incoming cash flows enables more effective cash management and allows firms to shape firms' planning based on forward-looking information. Although most firms are aware of the benefits of these forecasts, many still have difficulties identifying and implementing an appropriate prediction model. With the rise of machine learning algorithms, numerous new forecasting techniques have emerged. These new forecasting techniques are theoretically applicable for predicting customer payment behavior but have not yet been adequately investigated. This study aims to close this research gap by examining which machine learning algorithm is the most appropriate for predicting customer payment dates.

By using various machine learning algorithms, the authors evaluate whether customer payment behavior patterns can be identified and predicted. The study is based on real-world transaction data from a DAX-40 firm with over 1,000,000 invoices in the dataset, with the data covering the period 2017–2019.

The authors' results show that neural networks in particular are suitable for predicting customers' payment dates. Furthermore, the authors demonstrate that contextual and logical prediction models can provide more accurate forecasts than conventional baseline models, such as linear and multivariate regression.

Future cash flow forecasting studies should incorporate naïve prediction models, as the authors demonstrate that these models can compete with conventional baseline models used in existing machine learning research. However, the authors expect that with more in-depth information about the customer (creditworthiness, accounting structure) the results can be even further improved.

The knowledge of customers' future payment dates enables firms to change their perspective and move from reactive to proactive cash management. This shift leads to a more targeted dunning process.

To the best of the authors' knowledge, no study has yet been conducted that interprets the prediction of incoming payments as a daily rolling forecast by comparing naïve forecasts with forecasts based on machine learning and deep learning models.

The purpose of this study is to evaluate the profit efficiency of decision-making units (DMUs) based on predicted future information to solve the lag problem of improvement benchmarks given by the traditional profit efficiency model.

This paper proposes a two-step profit efficiency evaluation method. The first step predicts the future input and output information of DMUs through the past time-series data, obtaining a likely production possibility set (PPS) and profit frontier for the next period. The second step calculates DMUs' profit efficiency based on the predictions obtained in the first step and provides predictive benchmarking for DMUs.

The empirical results show that the proposed method yields good solutions for the lag problem of benchmarks given in ex-post evaluation, enabling bank managers to use predicted future information to achieve better improvement. Besides, compared with the technical efficiency measure, profit efficiency can better reflect the financial situation of DMUs and give the specific gap between the evaluated and optimal DMU.

For bank managers, the authors' new technique is advantageous for grasping the initiative of development because this technique accounts for the future development of the whole industry and sets forward-looking targets. These advantages can help banks improve in a more favorable direction and improve the asset management ability of banks.

This paper combines the data envelopment analysis (DEA) profit efficiency model with performance prediction and proposes a new two-step profit efficiency model, filling a gap in previous studies.

The authors have carried out a research project on artisanal salt activity in the Gulf of Cadiz, providing a new vision of the theories of intangible cultural heritage. The main objective has been to characterise artisanal salt activity in terms of its cultural and sustainable values, a perspective that had not been addressed until now. Moreover, the replacement of this activity by a more industrialised one has contributed to problems in the preservation of this heritage and a transformation of its places.

The research has combined qualitative methodology, based on observation and fieldwork, with a statistical review of the phenomenon under study. Finally, the data has been triangulated to understand the heritage and sustainable value, as well as its historical evolution.

All this contributes to understanding the importance of artisanal salt activity as an element of the intangible cultural heritage of the region, for the conservation of biodiversity and sustainable ways of life in the marshes of the Gulf of Cadiz, and the possibility of preserving it in the face of the problems of globalisation.

To date, there has been no research that combines sustainability and heritage in the field of salt activity. Likewise, until this study was carried out, there had been no research on salt activity from the perspective of intangible cultural heritage.

The interpretation of any emerging form or period in art history was never a trivial task. However, in the case of digital art, technology, becoming an integral part, multiplied the complexity of describing, systematizing and evaluating it. This article investigates the most common metadata standards for the documentation of art as a broad category and suggests possible next steps toward an extended metadata standard for digital art.

Describing several techno-cultural phenomena formed in the last decade, manifesting the extendibility of digital art (its ability to be easily extended across multiple modalities), the article, at first, points to the long overdue need to re-evaluate the standards around it. Then it suggests a deeper analysis through a comparative study. In the scope of the study three artworks, The Arnolfini Portrait (Jan van Eyck), an iconic example of the early Renaissance, The World's First Collaborative Sentence (Douglas Davis), a classic example of early Internet art and Fake It Till You Make It (Maya Man), a prominent example of the blockchain art, are examined following the structure of the VRA Core 4.0 standard.

The comparative study demonstrates that digital art is more multi-semantic than traditional physical art, and requires new taxonomies as well as approaches for data acquisition.

Acknowledging that digital art simply has not yet evolved to the stage of being systematically collected by cultural institutions for documentation, curation and preservation, but otherwise, in the past few years, it has been at the front-center of social, economic and technological trends, the article suggests looking for hints on the future-proof extended metadata standard in some of those trends.

To understand the specificities of Cash-flow bullwhip in the context of major crises similar to that of COVID-19, to identify its financial impacts on the Moroccan FMCG companies, to establish the profile of the companies most affected by this CFB and finally to propose internal control mechanisms that should be put in place to mitigate the effects of Cash flow Bullwhip in such a context.

The authors chose to conduct descriptive research on companies operating in the fast-moving consumer goods sector in Morocco. For this purpose, a survey was conducted on a target population during the period from December 2020 to March 2021. To answer the different research questions, a multiple correspondence analysis (MCA) has been conducted on the 21 variables obtained from the survey questions.

Small and medium-sized companies are those that have been the most financially impacted. Indeed, the instability of the cash flow conversion cycle increased their working capital requirements and limited their self-financing capacity. To face this situation, those companies used alternative means to finance their operational activity by using their equities or bank loans.

Due to the originality of the COVID 19 context, this study gives a different angle of view to analyze the cash flow bullwhip and its implications on the financial health of companies.

This paper analyses changes in the activity pattern of Damascus city from late modern era (late Ottoman rule) to the contemporary era. The research objective is to explore the impact of the socio-historical process on the evolving morphological structure of the urban core and to draw implications for post-war reconstruction.

Space Syntax methodology was employed to trace the historical and morphological changes in the urban core of Damascus. The timeframe was divided into five periods covering the city's socio-political transformation and five maps depicting these periods. Local and global integration measures were used to analyse the changes in the urban core across each period. Normalised angular choice (NACH) measure was used to identify the changes in the city planning system.

The results revealed that the urban core corresponded to the main streets, which had socio-economic importance across history. However, introducing a new planning system influenced by Western planning ideals led to the creation of multi-morphological patterns. At the city level, the study found that the urban core was more accessible in the preplanned areas, while the organic expansion of the informal settlements was exclusive of the core area. At the local level, some informal settlements showed an intense core. Intelligibility analysis revealed that earlier periods showed considerably higher values, implying declines in the ease of navigation of the city over time.

This study did not account for the political, economic and cultural factors that could shape morphological changes in Damascus. In addition, the study adopted historical reference points to understand the morphological changes, as high-quality geospatial data was not available to monitor the recent post-war situation.

The research findings give a foundation for a more contextualised historical understanding of spatial structure and changes, which can contribute to the post-war reconstruction and redevelopment of Damascus city.

To the best of the authors’ knowledge, this paper is the first to trace historical spatial changes in Damascus from a space syntax approach, weaving together socio-historical and configurational studies. In doing so, it shows how historically informed and spatially aware urban planning and design policies can support policymakers and built environment professionals in planning and redevelopment.

Research studies related to sustainability and green building have made monumental contributions to the concept of sustainable construction (SC) in Nigeria. This paper therefore aims to present a historical review of the development of SC in Nigeria over a 10 year period. The review also provides constructive perspective on the benefits of SC and the present state of enforcement of green building in Nigeria.

A historical review strategy was applied to the study. Using secondary data sources, 47 influential journals from emerald, scopus and science direct database focusing on “SC”, “sustainability” and “green building” in Nigeria between 2012 and 2022 were used for the analysis.

The analysis deduced that the development of SC in Nigeria have undergone a triple period of development: the inception period (2012–2016), the transition period (2016–2020) and the advancement period (2020–present). The review juxtaposes the three timeline to show rapid growth in the awareness of SC, but revealed moderate levels of implementation in some major cities in Nigeria. Therefore, the author finds and argues that the advancement of SC in Nigeria can be achieved through the synergy, commitment and active roles of researchers, academics, practitioners, policy makers and the government in enforcing existing green policies.

The study is the first academic paper to undertake a decade long historical review of SC in Nigeria. This review provides an up-to-date understanding of the developments, changing dynamics and future progressions in the field of SC in Nigeria.