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The purpose of this study is to present an analysis of the Islamic good governance concept and means known as Al-Siyasah Al-Syar’iyyah as a principle and approach for combating corruption. This literature review aims to synthesize extant literature that discusses the determinants of integrity and how to prevent and combat corruption based on the Al-Siyasah Al-Syar’iyyah perspective.

A systematic search was conducted on a literature review based on Scopus and referred journals from Google Scholar databases. A manual search on Google Scholar was performed to identify additional relevant studies. Studies were selected based on the predetermined criteria. They were thematically examined using content analysis.

The study found that most of the 45 works of the literature, (41 studies and four chapters) suggested that corruption should be considered a sin and that education of Al-Siyasah Al-Syar’iyyah’s perspective against corruption, emphasizing the principle of piety, the institutionalization of justice and accountability, good governance performance with an emphasis on its belief in self-accountability and justice, is the means to combat corruption.

This study is unique in that it focuses on locating material on battling corruption from the standpoint of Al-Siyasah Al-Syar’iyyah. Based on the al-Quran, the Sunnah and the best practices of Muslim rulership, this notion provides an epistemological, ethical and ontological stance in Islam.

In recognising the key role of business intelligence and big data analytics in influencing companies’ decision-making processes, this paper aims to codify the main phases through which companies can approach, develop and manage big data analytics.

By adopting a research strategy based on case studies, this paper depicts the main phases and challenges that companies “live” through in approaching big data analytics as a way to support their decision-making processes. The analysis of case studies has been chosen as the main research method because it offers the possibility for different data sources to describe a phenomenon and subsequently to develop and test theories.

This paper provides a possible depiction of the main phases and challenges through which the approach(es) to big data analytics can emerge and evolve over time with reference to companies’ decision-making processes.

This paper recalls the attention of researchers in defining clear patterns through which technology-based approaches should be developed. In its depiction of the main phases of the development of big data analytics in companies’ decision-making processes, this paper highlights the possible domains in which to define and renovate approaches to value. The proposed conceptual model derives from the adoption of an inductive approach. Despite its validity, it is discussed and questioned through multiple case studies. In addition, its generalisability requires further discussion and analysis in the light of alternative interpretative perspectives.

The reflections herein offer practitioners interested in company management the possibility to develop performance measurement tools that can evaluate how each phase can contribute to companies’ value creation processes.

This paper contributes to the ongoing debate about the role of digital technologies in influencing managerial and social models. This paper provides a conceptual model that is able to support both researchers and practitioners in understanding through which phases big data analytics can be approached and managed to enhance value processes.

The data used to present this case was collected from secondary data sources. These sources included media reports associated with Michael Jordan and his trajectory since entering the sport, as well as specific information published about his time at the Chicago Bulls. Another key source of information is the ESPN documentary conducted specifically on Jordan’s relationship with his National Basketball Association (NBA) team.

The case follows the story of Michael Jordan, who took his team, the Chicago Bulls, to fame in a rather controversial manner. To do so, Michael Jordan had to alter his leadership style over the years to be respected as a leader and motivate his team to win one NBA championship after another. On 20th April 2020, ESPN’s “The Last Dance”, a 10-part documentary about Michael Jordan and his time playing for the Chicago Bulls was released to much acclaim. The documentary became highly noted as Jordan himself, both directed and starred in the documentary. Jordan’s great achievements stood out, but so did the conflicts that the basketball star had with The Bulls’ management team and mainly, his teammates. Relationships between teammates were far from harmonious, which led to questions around whether Michael Jordan was as good a leader, as he was a star player. Cultural change within the organisation was primarily linked to the often-contested leadership of Jordan.

The case can be used at UG, MSc and MBA levels. It works for in-person teaching and for online teaching. It is most suitable in leadership, strategy and strategy in practice courses. However, it is critical to note that the case can shed light on the dynamics that leaders and teammates have within their teams. Therefore, this case may be valuable to students studying courses where they themselves must work in groups and oftentimes encounter challenges in managing their team. These challenges can arise at all levels of experience. As such, the case provides particularly useful reflection for decision makers who may be beginning to develop their leadership skill (UG), those who have already experienced working in teams (MSc) or leading teams themselves (MBA, Executive MBA). The case addresses the challenges associated with achieving high team motivation and performance. It also sheds light on the challenges associated with leading a cultural change within a team and the approaches of different actors involved. It may be best to introduce the case in the context of a (1.5–2 h) workshop once students understand the basic frameworks and tools used to analyse leadership styles and their characteristics.

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

To provide human judgment input for computer algorithm development, this study examines the relative importance of source, content, and style cues in predicting the truthfulness ratings of two common types of online health information: news stories and institutional news releases.

This study employed a multi-method approach using (1) a manual content analysis of 400 randomly selected online health news stories and news releases from HealthNewsReview.org and (2) an online experiment comparing truthfulness ratings between news stories and news releases.

Using content analysis, the authors found significant differences in the importance of source, content, and style cues in predicting truthfulness ratings of news stories and news releases: source and style cues predicted truthfulness ratings better than content cues. In the experiment, source credibility was the most important predictor of truthfulness ratings, controlling for individual differences. Experts have higher ratings for news media stories than news releases and lay people have no differences in rating the two news formats.

It is important for health educators to curb consumer trust in misinformation and increase health information literacy. Rather than solely reporting scientific evidence, educators should focus on addressing cues people use to judge the truthfulness of health information.

This is the first study that directly compares human judgments of health news stories and news releases. Using both the breadth of content analysis and experimental causality testing, the authors evaluate the relative importance of source, content, and style cues in predicting truthfulness ratings.

The current study examined Israeli researchers from various disciplines concerning their perceptions, attitudes and awareness of scientific publications in open access (OA) journals and repositories.

A survey instrument was developed and distributed to 202 Israeli researchers from universities, colleges and research institutions. The study used the united theory of acceptance and use of technology (UTAUT) model as a tool for mapping the factors known to influence researchers to publish in OA journals and repositories.

The empirical model confirmed the mediating effect of the association between researchers’ perceptions and the actual publishing in OA, through their behavioral intentions (BI). Furthermore, the BI are mediated by researchers’ self-decision to publish in OA. More specifically, a researcher's publication level in OA depended not only on the positive attitudes (Atti), performance expectancy (PE) and social influence (SI) mediated by BI, but also on conditions that support researchers who publish in OA, and disciplinary affiliation to science, technology, engineering and math (STEM) which lead the researcher to voluntarily publish in both green and gold OA.

This study contributed to the cumulative understanding of OA publishing by formulating and validating an empirical research model of acceptance and use.

The implications of the findings for scientific publication theory and practices are discussed.

The study suggests an effective framework to understand the researcher's final decision to publish in OA. This study's results are an essential step towards the cumulative understanding of OA publicity adoption and use by researchers as a global issue in general and in Israeli academic institutions in particular.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.