Search results

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

The current research aims to answer the following question: To what extent and under what conditions does hiring consultants to implement a customer relationship management (CRM) system produce performance gains for companies? To answer this question, this research delves into the critical interdependent roles of CRM consultant resources (CR) and user involvement (UI) in overcoming CRM’s technological and organizational implementation challenges.

A quantitative field study methodology was used to empirically test the research hypotheses. Cross-sectional data (N = 126) were collected from large client companies using CRM technology. Partial least squares-structural equation modeling was used to estimate the significance levels of the structural model.

The findings indicate that the extent to which CRM consultants improve CRM system quality (SQ) and, ultimately, firm performance, largely depends on UI, which acts as the key facilitating mechanism to cope with application complexity (APP) and requirements uncertainty (REQ).

This research probes into the largely unexplored interactions between CRM CR, UI, APP and REQ. Using these parameters, this model successfully predicts CRM SQ and firm performance.

This paper aims to explore the impact of salespeople’s goal orientation and self-regulatory mode on their performance through sales ambidexterity and sales technology infusion (STI) using a sales technology ecosystem approach.

This paper adopts a qualitative methodology, through in-depth interviews with salespeople from a diverse range of industries, age profiles and contexts, to explore the narratives and original meanings related to their goal orientation, self-regulatory mode, ambidexterity, STI and performance.

Sceptics are salespeople who may fear or hesitate to fully use the sales technology, whereas enthusiasts are ambidextrous salespeople with high STI, who are more open to change and able to face uncertainty, regardless of the differences in their background in terms of industry, age and experience.

STI may be influenced by individual factors, such as the salesperson’s goal orientation and self-regulatory mode. Hence, sales organizations should try to foster and facilitate further STI and sales ambidexterity, which are key to achieving positive outcomes in today’s technology-intensive sales settings.

This paper extends the current literature on sales technology and sales ambidexterity within a sales technology ecosystem perspective and provides new insight on the combined impact of these variables on the salesperson’s performance.

Sustainable customer relationship management (SCRM) is a combination of business strategy, customer-oriented business processes and computer systems that seeks to integrate sustainability into customer relationship management. The purpose of this paper is to contribute to the body of knowledge of marketing, business management and computer systems research domains by classifying in research categories the current state of knowledge on SCRM, by analysing the major research streams and by identifying a future research agenda in each research category.

To identify, select, collect, synthesise, analyse and evaluate all research published on SCRM, providing a complete insight in this research area, the PRISMA methodology, content analysis and bibliometric tools are used.

In total, 139 papers were analysed to assess the trend of the number of papers published and the number of citations of these papers; to identify the top contributing countries, authors, institutions and sources; to reveal the findings of the major research streams; to develop a classification framework composed by seven research categories (CRM as a key factor for enterprise sustainability, SCRM frameworks, SCRM computer tools and methods, case studies, SCRM and sustainable supply chain management, sustainable marketing and knowledge management) in which academics could expand SCRM research; and to establish future research challenges.

This paper have an important positive social and environmental impact for society because it will lead to an increase in the number of green and socially conscious customers with an ethical behavior, while also transforming business processes, products and services, making them more sustainable.

Customer relationship management in the age of sustainable development is an increasing research area. Nevertheless, to the authors' knowledge, there are no systematic literature reviews that identify the major research streams, develop a classification framework, analyse the evolution in this research field and propose a future research agenda.

The motivation for this study comes from decision making related to strategic marketing orientations in international markets. The authors examine if customer orientation and customer relationship orientation perform as two distinct constructs in driving firm innovativeness, and how together they support business growth among export firms. This study aims to suggest a customer-centric strategy for export firms that drive innovativeness and growth.

An international corporation specialized in company information services provided a list of the contact information of Italian companies. The authors sent an email request to respond to an online survey and received 416 effective responses from firms operating in export markets. The authors propose and empirically test a model in which customer orientation, customer relationship orientation and innovativeness predict business growth. This model controls for the effects of firm size, industry and customer type (B2B vs. B2C).

The study findings suggest that customer orientation and customer relationship orientation are two distinct strategic orientations driving innovativeness. However, they do not directly affect business growth. Instead, they require the innovativeness of an exporter to materialize as business growth.

The results of the study recommend business strategies focusing not only on customer needs and satisfaction but also on retaining current customers and building customer relationships in international markets. Firms can learn from international customers and develop effective customer-centric strategies to spread the acquired information into the internal decision-making as it contributes to firm innovativeness and business growth in international markets.

This study is one of the pioneering studies combining customer orientation and customer relationship orientation, showing their theoretical and empirical divergence. This study is also among the first which tests how the two strategic orientations together with innovativeness promote business growth among export firms. The authors add understanding of the synergistic effects both of using customer information and developing deeper relationships on firm innovativeness and performance among exporters.

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。