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It has been demonstrated in the US market that expected market excess returns can be predicted using the average higher-order moments of all firms. This study aims to empirically test this theory in emerging markets.

Two measures of average higher moments have been used (equal-weighted and value-weighted) along with the market moments to predict subsequent aggregate excess returns using the linear as well as the quantile regression model.

The authors report that both equal-weighted skewness and kurtosis significantly predict subsequent market returns in two countries, while value-weighted average skewness and kurtosis are significant in predicting returns in four out of nine sample markets. The results for quantile regression show that the relationship between the risk variable and aggregate returns varies along the spectrum of conditional quantiles.

This is the first study that investigates the impact of third and fourth higher-order average realized moments on the predictability of subsequent aggregate excess returns in the MSCI Asian emerging stock markets. This study is also the first to analyze the sensitivity of future market returns over various quantiles.

The global economy is plagued by an unprecedented shock that has devastated economic growth under the coronavirus pandemic. The prolonged movement control orders, social distancing, and lockdowns have triggered the global economic downturn, disrupted the demand and supply chains, reduced the pool of workforce, and caused many jobs loss. This paper aims to analyze the global economic cost of the coronavirus pandemic, and its current and future implications.

Based on contingency theory, this paper provides an in-depth analysis of the current situation on the global economic cost of the COVID-19 outbreak and gives insights from an organizational perspective.

This paper found that the world has witnessed far-ranging economic consequences due to the coronavirus pandemic in four aspects: (i) decline in personal consumption; (ii) decline in the investments and stock prices in capital market; (iii) decline in government spending in developmental projects and increase in new borrowing; and (iv) decline of exports of goods to international markets.

The novelty lies in investigating the effects of the COVID-19 pandemic on micro and macroeconomic levels — the components of GDP, consumer behavior, business investments, government spending, and global exports. The paper suggests the need for urgent actions by the world leaders to oversee, anticipate, and manage the risks and cushion the economic consequences. It concludes that the flexibility and adaptability of leaders, effectiveness, workforce protection, efficient use of modern technology, including automation and artificial intelligence, would enhance the resilience of supply chains which will support organizations to sustain in this critical time.

With theoretical underpinnings in the conservation of resources theory, this research aims at understanding the link between workplace ostracism (WPO) and its effects on customers' interests in the context of COVID-19, with the mediation of stress and moderation of self-efficacy (SE).

The study followed a time-lagged design. A sample of 217 frontline employees working in the food sector of southern Punjab, Pakistan, responded to the study questions using the survey method with structured questionnaires. A Statistical Package for the Social Sciences (SPSS) tool was utilized for data analysis with bootstrapping and PROCESS macro.

The findings show that an important mechanism by which ostracism translates into customer service sabotage (CSS) is the increase in perceived stress levels of the employees. Additionally, SE was found to be an important personal resource that acts as a moderator in the said relationship.

Employees with high SE sense less workplace stress even during a pandemic. Leadership should consider the stress-alleviating effect of SE for lessening the damaging influence of WPO on customers.

The study fills an important empirical gap in the context of the COVID-19 pandemic, by showing that due to resource loss perceived by employees while being targeted by ostracism, they may decide to transfer their frustration towards organizational customers by sabotaging their service experience.

The high dropout rate among online learning students is a serious issue. Using the theory of planned behavior as a framework, this study investigates what effect attitude, opinion of others and perceived ease of online learning technologies leave on Pakistani online students' persistence intentions.

The sample of this study comprises 320 students enrolled at a distance learning university in Pakistan. Online questionnaires are used to gather data for the study. Correlations and regression analysis are run to figure out the effect of independent variables on the dependent variable of the study.

The findings of the study show that 51% variance in online students’ persistence intentions can be explained by personal attitude, subjective norms and perceived behavioral control.

The use of a non-random sampling technique along with a cross-sectional design form the major limitations of the study.

The outcome of the study may help online education providers as well as policymakers to design programs and initiatives to improve students’ retention in online study programs.

The study contributed to the extant literature by finding out Pakistani online students’ persistence behavior is affected by their attitude, subjective norms and perceived ease of online learning. The study also found that the opinion of people closely related to students influences their study persistence decisions.

Over the years, shrines have been ignored as a destination by islamic marketing scholars. However, shrines can be classified as Islamic spiritual destinations which are visited by people to serve various purposes. Moreover, in the country context of Pakistan with its beautiful cultural traditions and the religiousness among people, the visit to a shrine as a destination experience is scantly examined. This study fills this void and aims at exploring Muslim tourists' spiritual experiences of visiting shrines as Islamic spiritual destinations.

An interpretive qualitative inquiry is used based on phenomenology as the leading methodology for this exploration. Following a purposive sampling technique, researchers interviewed 10 informants who regularly visit shrines. The collected data are analyzed based on thematic analysis.

The results of a thematic analysis reveal six themes that emerged from tourists' experiences of Islamic spiritual destinations. These include: religious and spiritual values, spiritual belief system, commercial experience, hospitality and support experience, socialization experience and obstruction experience.

The findings of this study can be used by policymakers managing Islamic tourist destinations. It will help them to improve tourist experiences.

The findings contribute to both theory and practice of destination marketing by exploring the factors influencing tourists' perceptions about their experience of Islamic spiritual destinations.

This paper aims to examine the structure and content of religious tourism destination image through the reviews of visitors to Makkah and Medina, two of the world’s most popular Muslim pilgrimage sites.

This is an exploratory netnographic study of the 913 reviews posted on TripAdvisor from 2018 to 2022. The structure (dimensions and attributes) and content (variables) comprising the construct of religious tourism destination image emerge through manual thematic analysis and confirmed through content analysis.

Religious tourism destination image is a three-dimensional – cognitive, affective and conative – construct comprising both religion-specific, generally sacred and secular variables in a single, indivisible crystallization of experience.

Destination marketing organizations and marketers of tourism enterprises should regularly analyze visitor reviews posted on social media and carefully manage all variables of the religious tourism destination image, specifically stressing the religious aspect.

To the best of the authors’ knowledge, this is the first systematic analysis of the structure and content of religious tourism destination image based on detailed consumer evaluations and unprompted storytelling.

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。