Search results

Recent research suggests that more than two-thirds of people use online reviews to find a new primary care physician (PCP). However, it is unclear what role review content plays when a patient uses online reviews to decide about a new PCP. This paper aims to understand how a review's content, related to competence (communication and technical skills) and benevolence (fidelity and fairness), impacts patients’ trusting intentions to select a PCP. The authors build the model around information diagnosticity, construal level theory and valence asymmetries and use review helpfulness as a mediator and review valence as a moderator in this process.

The authors use two experimental studies to test their hypotheses and collect data through prolific.

The authors find that people have a harder time making inferences about the technical and communication skills of a PCP. Reviews about fidelity are perceived as more helpful and influential in building trust than reviews about fairness. Overall, reviews about the communication skills of a PCP have stronger effects on trusting intentions than other types of reviews. The authors also find that positive reviews are perceived as more helpful for the readers than negative reviews, but negative reviews have a stronger impact on patients' trust intentions than positive ones.

The authors identify how online reviews about a PCP’s competency and benevolence affect patients’ trusting intentions to choose the PCP. The implication of findings of this study for primary medical practice and physician review websites is discussed.

This study aims to analyze and predict a user’s behavior and create recommender systems in libraries and information centers, using data mining techniques.

The present study is an analytical survey study of cross-sectional type. The required data for this study were collected from the transactions of the users of libraries and information centers in Hamadan University of Medical Sciences. Using data mining techniques, the existing patterns were investigated, and users’ loan transactions were analyzed.

The findings showed that the association rules with the degree of confidence above 0.50 were able to determine user access patterns. Furthermore, among the decision tree algorithms, the C.05 predicted the loan period, referrals and users’ delay with the highest accuracy (i.e. 90.1). The other findings on feedforward neural network with R = 0.99 showed that the predicted results of neural network computation were very close to the real situation and had a proper estimation of user’s delay prediction. Finally, the clustering technique with the k-means algorithm predicted users’ behavior model regarding their loyalty.

The results of this study can lead to providing effective services and improve the quality of interaction between librarians and users and provide a good opportunity for managers to align supply of information resources with the real needs of users.

The results of the study showed that various data mining techniques are applicable with high efficiency and accuracy in analyzing library and information centers data and can be used to predict a user’s behavior and create recommendation systems.

The study aims to investigate how recommender systems shape providers’ dynamics and content offerings on platforms, and to provide insights into algorithm designs for achieving better outcomes in platform design.

This study employs a multi-agent simulation framework coupled with reinforcement learning models to examine the influence of different recommender system designs on providers’ perception of demand and platform content.

The study reveals that recommender systems have the potential to introduce biases in providers’ understanding of user preferences, thereby impacting the variety of offerings on platforms. Moreover, it identifies algorithm design as a critical factor, with item-based collaborative filters showcasing superior performance in contexts where customers exhibit selectivity. Conversely, user-based models prove more effective in scenarios where recommendations significantly sway user decisions, ultimately boosting sales.

In practical terms, these insights can guide platform developers in making informed decisions regarding the selection and implementation of recommender system algorithms. By tailoring algorithm choices to specific contexts, platforms can enhance user welfare, ultimately leading to improved platform performance and profitability.

The findings underscore the importance of integrating provider dynamics and algorithmic biases into the design of recommender systems and platforms. This highlights avenues for future research to explore and refine our understanding of these dynamics.

This study’s fundamental objective is to assess climate change impact on reference evapotranspiration (ET_o) patterns in Egypt under the latest shared socioeconomic pathways (SSPs) of climate change scenarios. Additionally, the study considered the change in the future solar radiation and actual vapor pressure and predicted them from historical data, as these factors significantly impact changes in the ET_o.

The study utilizes data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models to analyze reference ET_o. Six models are used, and an ArcGIS tool is created to calculate the monthly average ET_o for historical and future periods. The tool considers changes in actual vapor pressure and solar radiation, which are the primary factors influencing ET_o.

The research reveals that monthly reference ET_o in Egypt follows a distinct pattern, with the highest values concentrated in the southern region during summer and the lowest values in the northern part during winter. This disparity is primarily driven by mean air temperature, which is significantly higher in the southern areas. Looking ahead to the near future (2020–2040), the data shows that Aswan, in the south, continues to have the highest annual ET_o, while Kafr ash Shaykh, in the north, maintains the lowest. This pattern remains consistent in the subsequent period (2040–2060). Additionally, the study identifies variations in ET_o , with the most significant variability occurring in Shamal Sina under the SSP585 scenario and the least variability in Aswan under the SSP370 scenario for the 2020–2040 time frame.

This study’s originality lies in its focused analysis of climate change effects on ET_o, incorporating crucial factors like actual vapor pressure and solar radiation. Its significance becomes evident as it projects ET_o patterns into the near and distant future, providing indispensable insights for long-term planning and tailored adaptation strategies. As a result, this research serves as a valuable resource for policymakers and researchers in need of in-depth, region-specific climate change impact assessments.

The purpose of this paper is to investigate relationships among dependence, trust, and integration in the Chinese 3PL context. 3PL integration is manifested in two key dimensions: information sharing and process coordination.

This study develops a dependence-trust-3PL integration-performance model and tests it using structural equation modeling with survey data collected from 361 companies in the Greater China area (i.e. mainland China, Hong Kong, and Taiwan).

The results show that switch dependence is indirectly related to information sharing and process coordination through goodwill trust, while goal dependence has direct links with both integrative behaviors. The authors also found that only goodwill trust mediates the relationship between dependence and integrative behaviors, while ability trust does not mediate any relationships. Finally, the analysis validated the direct link between process coordination and financial performance, but did not find a significant link between information sharing and financial performance.

Different from most previous studies on similar topics, this study examines the impacts of different types of dependence and trust on different 3PL integration dimensions. As a result, the findings are more specific and have direct relevance to effective 3PL relationship management in China.

The generality of the universe is “everything.” In this regard, the Qur'an declares abundantly on the ultimate and perfect domain of the divine law in creation. This also means the profundity of the divine law in explaining and applying to all things in the knowledge–time–space dimensions of the conscious universe. Such observations or insights that span the complete universe comprise the Signs of Allah (ayath Allah).¹

This chapter approaches the topic of teaching the Western scholarly tradition in non-Western countries like the United Arab Emirates (UAE) from three perspectives employing the following metaphors: as a Public Servant motivated by public service to the goals and aims of the country’s development articulated by UAE rulers and its citizens; as Cultural Diplomat, representing the Western tradition and its scholarly achievements while respecting other traditions; and as Intellectual Imperialist, aiming at a colonising incorporation of the UAE into the Western academic world.

The main methodology adopted is the Weberian ideal type, located within a comparative and historical context that produces the metaphors as analytically possible perspectives as a western expatriate faculty member. Additional critique is drawn from Bourdieu, Said, Freire, Giroux, Foucault, Goffman and cross-cultural organisation studies.

The findings consist of an analytic framework consisting of public servant, cultural diplomat and intellectual imperialist as a set of conceptions for analysing possible orientations of Western expatriate academics in developing countries.

The implications are threefold: on a personal level, what experientially does each of the metaphors mean for one’s sense of identity, profession, values and relationships; on a pedagogical level, what principles and values distinguish the curriculum and teaching styles as well as orientation to Arab and Islamic scholarship; and politically, what is the potential impact and unintended consequences for the indigenous culture, sovereignty and societal survival of a country under the heavy influence of globalisation. The contention of this chapter is that one cannot avoid adopting one or more of these roles and may even perform in contradictory ways.

The originality is in establishing a new set of analytic categories drawing on post-colonial, diplomacy and critical studies.

The growth and development of positive psychology approaches in the areas of human resource management has created a successful conceptual basis in the psychology of business and jobs and has led to a tendency to apply knowledge and skills to job expectations in line with job expectations. That profession will grow, and this can also lead to the development of ethical practices. The purpose of this paper is the effect of self-fulfilling prophecy on developing auditors' ethical values.

The target population of this study was auditors of auditing organizations and private sector audit firms that were selected through random sampling and evaluated over a period of 6 months. The research instrument was standard questionnaires, and partial least squares analysis was used to test and test the research hypotheses.

The results of this study show that the effect of self-fulfilling prophecy on ethical virtue and ethical conscientiousness as two dimensions of auditors' ethical values has a positive and significant effect.

This study explains how to clearly convey the social expectations of an auditor about value-based approaches in the audit profession, and it examines the role of these expectations in the professional performance of auditors. In fact, beliefs and expectations play a decisive role in improving auditors' level of value based on professional behavior, such as professional skepticism and objectivity, and this research can help increase the level of knowledge about this profession.

Existing research on collaborative innovation mechanisms from the perspective of global operation is very limited. This paper aims to address the research gap by studying the factors influencing globally distributed teams’ innovation performance, especially how effective knowledge sharing between distributed teams promotes collaborative team innovation.

This research proposes a model to investigate how collaborative knowledge sharing affects global operations [team dispersion, task orientation, information and communication technology (ICT) usage] and innovation performance based on the data collected from 167 managers in 40 local Chinese IT and offshoring firms. Using the theory of Cognitive Diversity and Innovation Diffusion and Synergy, separate hierarchical regression analysis was used to test the proposed model.

The findings of this study demonstrate that effective collaborative knowledge sharing plays a crucial role in enhancing innovation performance in a global operation. Specifically, innovation capacity can be improved by task orientation, ICT usage and team dispersion.

This research study contributes to the development of global distributed operations and innovation among distributed teams in multinational corporations.