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Based on the dynamic capabilities view, the current study aims to empirically investigate the effects of organizational learning culture (OLC), strategic reconfiguration (SREC) and digital transformation (DT), altogether, on Egyptian private hospitals' strategic renewal in the face of the COVID-19 pandemic.

This study adopted a cross-sectional design to collect the data used to carry out mediation analysis. A self-administered questionnaire was used to collect data from a sample consisted of 264 Egyptian private hospitals. The smart partial least square structural equation modeling technique (PLS-SEM) was adopted to test the hypotheses.

The results demonstrate that OLC directly and positively affects SR. Besides, SREC and DT partially and serially mediate the OLC-SR relationship.

The sample size was small, covering only Egyptian private hospitals. The results may be different in the manufacturing sector and in other countries. The study was cross-sectional which is limited to trace long-term effects of OLC, SREC and DT on SR. Accordingly, a longitudinal study may be undertaken.

Private hospitals' managers must actively explore and dig out valuable resources in order to discover potential information and trends endeavor to redesign internal structures, and reconfigure their current resources, structures and strategies to achieve strategic renewal. The findings also provide new insights to mangers of private sectors' institutions and direct their attention toward adopting the strategic renewal option to survive amidst crises instead of retrenchment, persevering, or quitting business.

The study's results imply that health care providers have sought to improve the capacities of their health care systems to address the patient-level social needs through continuous learning, internal reconfigurations and the transformation toward digitalization to renew their services.

This study therefore contributes to SR literature by being the first empirical study to introduce an integrative model for the antecedents of SR amidst the pandemic.

Among the many fashionable management terms, empowerment refers to a change strategy with the objective of improving both the individual’s and the organization’s ability to act. Reviews the various themes of empowerment with particular reference to articles published between 1994‐1996 in the journal Empowerment in Organizations. The main themes are: creating an empowerment culture; empowerment as a management strategy; training and development for empowered employees; empowered teams and implementation techniques and empowerment and organizational change in the hospitality industry.

We have daily tangible evidence that our air is more polluted, our water less drinkable, our oil and minerals less plentiful, our physical surroundings less pleasant to the eye, the ear, and the nose. These confrontations present us with very concrete problems to solve. The consequences of not taking action can be quite clearly spelled out and understood and predicted.

Increasingly there has been a blurring of the boundaries between competition and cooperation in many sectors of the global economy. This trend has not escaped the tourism industry. Indeed, numerous examples exist where major players in the transportation, accomodation, and telecommunications sectors have joined forces.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

Human resources are of great importance to provide competitive advantage in tourism, which is a labour-intensive industry. It is seen that the level of organizational commitment of the individuals who have similar values with the organization they work for and who can fulfil the roles and duties they undertake and who can meet all their needs in return increases. Their level of alienation is also observed to decrease. Population of the study, which purposes to reveal whether organizational culture has any impact on the employees' perception of person-organization fit and their level of organizational alienation or not, constitutes 4- and 5-star hotels in service in the central district of Izmir province. According to the results, it was seen that hotel businesses had two types of organizational culture such as hierarchy and clan culture. In the hotels with clan culture, demands-abilities fit levels of the worker were higher than value-congruence and needs-supplies dimensions. It was seen that workers alienated on meaninglessness dimension mostly. Similarly, in the hotels with hierarchy culture, demands-abilities fit levels of the worker were higher than value-congruence and needs-supplies dimensions. Workers alienated from their organization on meaninglessness dimension mostly.

Using the social constructivist perspective of learning, this study aims to examine the patterns and the key areas of entrepreneurial learning based on a case study of 16 participants who were the incubatees of two technology-based business incubators in China. The key research question is: how do novice entrepreneurs, focusing on technology-based business incubators, learn from a social constructivist perspective?

The researchers applied a qualitative methodology in this study as they wanted to understand better the complexity of the learning process that is hard to achieve quantitatively. The qualitative data was collected through in-depth interviews with the incubatees, who were the managers and owners of their businesses. The interviews with the entrepreneurs were mainly focused on the learning patterns and the factors influencing learning through the use of the critical incident technique.

This will allow incubator managers to better evaluate the extent of effective entrepreneurial learning within the incubator's eco-system. The results show that the participants learn through socially constructivist systems that are structured around the support provided by the incubators. Learning in this context takes place in an extended spectrum, and participants are more interested in learning from networking with experienced entrepreneurs rather than from other incubatees or formal courses. Findings of this study help incubator managers and novice entrepreneurs to better shape learning and teamwork in an effort to improve the learning process. Policy makers should consider introducing schemes that encourage novice entrepreneurs to exhibit the creativity and innovation behaviour reported by experienced entrepreneurs.

The focus of this study is primarily on incubators as the context of learning, whereas the macro-environmental factors, such as the socio-cultural and regulatory environments in China, were considered as playing a subtle role and would affect the incubatees' learning indirectly. The paper is based on a relatively small sample size and is geographically located in Ningbo, China. As such, the authors call for further research for comparative studies with a larger sample size so that a possible theory of entrepreneurial learning in the context of incubators might emerge in the future.

Increasing market pressures require organizations to rethink the development of change capability. Building a sustainable and flexible organization capable of responding in a timely manner to quickly changing customer demands without compromising technological excellence and quality is a complex task. This chapter builds on a five-year study of transformation efforts at a product development unit of Ericsson. The complexity of designing and managing learning mechanisms as both a transformation engine and a way to improve new product development is captured. The chapter points toward the challenges of designing and managing learning mechanisms that enhance organizational agility.