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While most West European nations were formed around pre-existing entities that could be called “countries” before the modern age, this was not the case in the Middle East. Some entities, like Egypt, did have a clear political and cultural identity before colonialism, others, like Algeria, did not. This chapter discusses the four states of the Maghreb: Morocco, Algeria, Tunisia and Libya, through the perspective of “country creation” going into and coming out of colonial rule. We can see here two “models” of fairly similar types of historical development, one showing a gradual process through a protectorate period to relatively stable modern nations, another through violent conquest and direct colonization ending in violent liberation and military and wealthy but fragile states. The article asks whether these models for the history of country creation and the presence or absence of pre-colonial identities can help explain the modern history and nature of these states in the Arab Spring and the years thereafter. Then, a more tentative attempt is made to apply these models to two countries of the Arab east, Syria and Iraq. While local variations ensure that no model can be transferred directly, it can show the importance of studying the historical factors that go into the transition from geographical region to a country with people that can form the basis of a nation.

Manufacturing firms must embrace smart technologies and develop complex leadership approaches to achieve sustainability. Using the dynamic capability theory, this paper aims to examine the influence of the adoption of industry 4.0 technologies (AT) and paradoxical leadership (PL) on corporate sustainable performance (CSP) of manufacturing small-medium enterprises (SMEs) in Malaysia. Moreover, organisational ambidexterity (OA) is a mediator and strategic flexibility (SF) is a moderator in the study.

The study is a cross-sectional, quantitative study design that collected 395 usable responses through a simple random sampling technique and a close-ended structured questionnaire. Structural equation modelling (SEM) procedures were followed to analyse the data.

The statistical outcome implies that the AT significantly influence CSP and OA and mediate with CSP in the presence of OA. Moreover, PL shows a significant impact on OA, is insignificant on CSP and mediates with OA and CSP. The authors found a significant association between OA and CSP; however, SF did not provide evidence of a moderate effect.

The findings of this study clarify the role that organisational capabilities (OA, AT, PL and SF) play in fostering sustainability. The authors suggest incorporating SMEs from different geographies in other sectors by applying diverse methodologies and relevant constructs.

The result injects new perspectives into policy, managerial and individual levels. Installing OA, AT, PL and SF makes SMEs sustainable.

The empirical validation of the influence of OA and AT on CSP and the interaction of PL and SF enriches the organisational and entrepreneurial literature.

The purpose of this paper is to explore how sales compensation disclosure, salespeople’s perception of corporate social responsibility (CSR) toward customers (i.e. customer-focused CSR), regulatory knowledge and coworkers’ ethical behavior may influence life insurance salespeople’s moral intensity and intentions to engage in misleading sales behaviors.

The hypotheses are analyzed using partial least squares (PLS) regression with the data gathered from full-time life insurance salespeople in Taiwan.

The main findings indicate that disclosing sales compensations will alter the ethical decision-making process of life insurance salespeople. The findings further point out that customer-focused CSR is an important variable affecting moral intensity and ethical intentions.

There has not been any research on the effects of compensation disclosure on moral intensity and misleading sales behavior. The literature gap has led to a poor understanding of the relationship between the compensation disclosure policy and ethical sales behavior. Moreover, previous studies indicate that specific factors (such as moral intensity and ethical intention) are directly associated, while the research shows that as long as a regulatory policy (e.g. the policy of compensation disclosure) changes, the correlation between these variables may shift from significant to nonsignificant (or vice versa). The results are interesting enough to warrant more research, and they also show that the direct link between variables mentioned in previous research is not always stable or universal.

This paper aims to measure the intention to use digital marketing strategies to enhance the performance of tourism business as well as the extent of digital renovation applications in tourism for sustainable business in a new normal era.

This paper is an insight from the existing relevant literature on the tourism business from time immemorial. The conceptual framework of this study is designed based on previous studies of digital marketing practices for tourism businesses. Furthermore, data were collected from 270 respondents, of which the valid response rate is 72.97%. Partial least square (PLS)-structural equation modeling (SEM) is used to validate the conceptual framework and hypotheses testing.

Among the nine hypotheses path, seven were supported. This study result shows that perceived usefulness, perceived ease of use, social media marketing and tourism business performance are critical factors for adopting digital marketing in tourism. Thus, tourism service providers' intention has a positive impact to meet the expectation of tourists and adoption of digital marketing.

The study's results will assist tourism researchers and service providers in understanding an authentic relationship between digital practices of tourism business and tourist satisfaction. In addition, the legacy of tourism business through digital marketing empowers the owner and community.

The study is the first to explore the relationship between tourism business performance and digital marketing during the new normal era for the empowerment of local community and expanded business in tourism sector.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.