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In recent times the government has emerged as an enabling and empowering facilitator promoting the adoption of corporate social responsibility (CSR) by businesses to leverage economic competitiveness and growth. India provides a unique context to explore the mandated role of government in relation to CSR specifically within the context of understanding its effective use to resolve grand challenges which the country is facing at present. Grand challenges are complex social, economic and environmental problems which require innovative and collaborative solutions. In this chapter we explore extant secondary data, related to CSR and Sustainable Development Goals (SDGs) to examine whether mandatory CSR implementation which has been unfolding in India over the last few years has been effective in addressing India's grand challenges. Specifically, it focuses on the role of the Indian government, at the national and state levels, in directing CSR activities towards the SDGs.

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。

This study aims to provide more insight into how customer voice is captured and used in managerial decision-making at the marketing-finance interface. This study’s focus is on understanding how the customer voice, often communicated through online and social media platforms, is used in high-performing hotels.

This research is based on a case study of four high-performing Irish hotels. For each case, multiple informants, including marketing managers, general managers and finance managers, were interviewed and shadowed. Twenty seven decisions across the four cases were analysed to assess the use of customer voice in managerial decision-making.

Social media provides a stage that has empowered the customer voice because of the public nature of the interaction and the network effect. Customer voice is incorporated in managerial decision-making in three distinct ways – symbolically as part of an early warning system, for action-oriented operational decisions and to some extent in the knowledge-enhancing role for tactical decisions. While there is a greater appreciation among senior managers and the finance and accounting managers of the importance of customer voice, this study finds clear limits in its utilisation and more reliance on traditional finance and accounting data, especially in strategic decision-making.

The cases belong to a highly visible open environment of hotels in an industry where customer voice has immediate and strong effects. The findings may not directly apply to industries characterised by a relatively more closed context such as banking or insurance. Moreover, the findings reflect the practices of high-performing hotels and do not necessarily capture the practices used in less successfully operating hotels.

While marketers need to enhance their ability to create a narrative that links the customer voice to revenue generation, finance managers also need to develop a skillset and adopt a mindset that appropriately reflects the influential role for customer voice in managerial decision-making.

Despite the linkage of marketing performance to business performance, there is limited research on the impact of customer information on managerial decision-making. This research provides insight into how customer voice is considered at the critical marketing-finance interface.

This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.

Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools.

Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business’ organizational model. A key consideration is a “creative-possibility perspective,” highlighting the future potential to use AI not only for rational but also for creative thinking purposes.

This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a “creative-possibility perspective.”

A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013).

This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.

This study aims to explore the innovative strategies of business model of the free-to-fee switch, the relationship between the business model innovation and customer knowledge and further develop a conceptual model.

This study adopts a multiple case study method with abductive research logic, following the replication logic to select samples. A total of eight outstanding companies with altogether 312 free-to-fee switch events were selected from 1998 to 2021.

A strategic matrix with four innovative business models for the free-to-fee switch is generated. The parallelism between the models and customer knowledge orientations is also found. Further, the study develops the conceptual model regarding customer knowledge orientation as a key mediation.

The study highlights the conceptualization definition of customer knowledge orientation and its mediation effect to the business model innovation of free-to-fee switch, which is a new issue compared with previous research. Furthermore, it reveals that there exists organizational ambidexterity, which brings a new definition of customer knowledge orientation.

This study suggests how to integrate customer knowledge orientations to support the marketing process of the business model of free-to-fee switch. It also proposes a specific mechanism to conduct the free-to-fee switch with the introduction of four innovative strategic models and eight evolutional paths.

This study creatively proposes the strategic matrix and the conceptual model of business model innovation of free-to-fee switch. Moreover, a new conceptual definition of customer knowledge orientation is specified.

The purpose of this paper is to investigate the irrevocable role of cause-related marketing (CRM) and its research imperative, exploring its contemporary insights in and across international markets, toward scholarly and executive application.

This research is theoretical and it compiles and interrelates, in a multiperspective fashion, significant extant works in the field; focusing on how established and emergent variables and constructs can be leveraged, in order to develop insights into what does and does not work in international CRM.

Extant works on international CRM still present significant gaps pertaining to key questions. Furthermore, true understanding of CRM stems from comprehending consumers, both individually and collectively; and both their underlying and contextual motivators, factors and forces. This calls for a multiperspective and cross-disciplinary approach to CRM to that weaves in contextual (sociocultural, etc.) elements to the equation.

Limitations naturally pertain to the research's theoretical nature that requires empirical testing.

CRM offers consumers both the means and the ends of acquiring their target core value benefits, additionally or peripherally to their core purchase purpose; potentially making the difference between business/brand success and failure.

Through CRM, the contemporary consumer seeks product value benefits that transcend quality and functionality (etc.), to engulf abstract and intangible values pertaining to social, ethical, self-image and self-actualization factors.

The comprehensive review, contextual elucidations and cross-disciplinary perspectives of this paper originally present the scope, depth, complexity and gaps of the subject, and pave the way for the research that still needs to ensue.