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1 – 10 of 109Xiaosong Dong, Hanqi Tu, Hanzhe Zhu, Tianlang Liu, Xing Zhao and Kai Xie
This study aims to explore the opposite effects of single-category versus multi-category products information diversity on consumer decision making. Further, the authors…
Abstract
Purpose
This study aims to explore the opposite effects of single-category versus multi-category products information diversity on consumer decision making. Further, the authors investigate the moderating role of three categories of visitors – direct, hesitant and hedonic – in the relationship between product information diversity and consumer decision making.
Design/methodology/approach
The research utilizes a sample of 1,101,062 product click streams from 4,200 consumers. Visitors are clustered using the k-means algorithm. The diversity of information recommendations for single and multi-category products is characterized using granularity and dispersion, respectively. Empirical analysis is conducted to examine their influence on the two-stage decision-making process of heterogeneous online visitors.
Findings
The study reveals that the impact of recommended information diversity on consumer decision making differs significantly between single-category and multiple-category products. Specifically, information diversity in single-category products enhances consumers' click and purchase intention, while information diversity in multiple-category products reduces consumers' click and purchase intention. Moreover, based on the analysis of online visiting heterogeneity, hesitant, direct and hedonic features enhance the positive impact of granularity on consumer decision making; while direct features exacerbate the negative impact of dispersion on consumer decision making.
Originality/value
First, the article provides support for studies related to information cocoon. Second, the research contributes evidence to support the information overload theory. Third, the research enriches the field of precision marketing theory.
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Shixuan Fu, Xusen Cheng, Anil Bilgihan and Fevzi Okumus
Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions…
Abstract
Purpose
Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.
Design/methodology/approach
A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.
Findings
The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.
Originality/value
This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.
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Anuj Kumar, Nimit Gupta and Gautam Bapat
This paper aims to explore ChatGPT’s (generative pre-trained transformers) potential as a tool for retailers to improve customer experience and boost sales. While it provides…
Abstract
Purpose
This paper aims to explore ChatGPT’s (generative pre-trained transformers) potential as a tool for retailers to improve customer experience and boost sales. While it provides benefits like personalized recommendations and 24/7 assistance, there are limitations, like difficulty in understanding unconventional language. The paper stresses careful integration to overcome these limitations and create a better customer experience. Additionally, it discusses the potential for further development and integration of ChatGPT in retail, such as generating product descriptions and virtual try-on experiences. Finally, the paper encourages retailers to embrace ChatGPT to meet their customer needs.
Design/methodology/approach
Case-based methodology involves using specific cases or examples to explore a broader issue or phenomenon. Researchers have analysed real-world cases to identify patterns, themes and insights that can be applied to other contexts or situations. This was useful for understanding complex and multifaceted issues as it allowed us to delve deeper into specific examples and explore the nuances of the situation.
Findings
While ChatGPT is a powerful tool for retailers, limitations such as difficulty in understanding non-standard accents and unconventional language can arise, causing customer frustration. Retail managers must integrate ChatGPT in a way that enhances customer experience. In the future, ChatGPT has the potential to generate product descriptions, provide virtual try-on experiences and integrate with augmented or virtual reality technology to offer more immersive experiences. Careful consideration and integration can help retailers overcome these limitations and offer personalized recommendations, round-the-clock assistance and an engaging customer experience that improves sales.
Originality/value
The case topic is very much in a novel stage of research and writing.
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This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to…
Abstract
Purpose
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).
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.
Originality/value
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.
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Vibhav Singh, Niraj Kumar Vishvakarma and Vinod Kumar
E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind…
Abstract
Purpose
E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.
Design/methodology/approach
Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.
Findings
Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.
Research limitations/implications
TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.
Practical implications
The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.
Originality/value
Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.
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Online advertising becomes an essential tool to reach the target audience. One of the most widely used strategies is re-targeting. Firstly, this study explores the impact of…
Abstract
Purpose
Online advertising becomes an essential tool to reach the target audience. One of the most widely used strategies is re-targeting. Firstly, this study explores the impact of ethics, privacy and ads' perceived benefits (ad effectiveness and ad relevance) on consumers' attitudes toward online advertising. Secondly, the study investigates the mediating effect of attitudes toward re-targeting online advertising on consumers' purchase intentions. Finally, the study investigates the moderating effect of the perceived ethicality of re-targeting online advertising on consumers' purchase intentions.
Design/methodology/approach
Participants (n = 307) were recruited through an online survey platform (MTurk) in the USA. The sample consisted of 65% male and 35% female respondents. The majority are aged 25–34 years, followed by 35–44 years (20%), 45–54 years (14%), 18–24 years (8%) and 55 years and older (6%).
Findings
The results show that ad effectiveness and ad relevance influenced consumers' attitudes toward re-targeting. This study shows that consumers are willing to trade their privacy for better search quality. Moreover, perceptions toward the ethicality of re-targeting ads moderated the relationship between consumers' attitudes and purchase intentions.
Research limitations/implications
This study will make several contributions. First, the study will extend the consequential theory in the context of online advertising. Second, the study will assist companies in using re-targeting strategies. The results will reveal which factor is the most important factor impacting consumers' attitudes toward re-targeting strategies.
Originality/value
This is one of the first few papers investigating consumers' perceptions of the ethicality of re-targeting online advertising.
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K.S. Ranjani, Sumi Jha and Neeraj Pandey
After reading this case study, the students will be able to identify the various choices available in social e-commerce using network marketing, interpret data-driven decisions in…
Abstract
Learning outcomes
After reading this case study, the students will be able to identify the various choices available in social e-commerce using network marketing, interpret data-driven decisions in social e-commerce and evaluate their role in scaling business, analyse cost and revenue management in value segments, evaluate technology adoption among the masses using appropriate communication structures and develop customer relationships and manage their sentiments in the era of social media.
Case overview/synopsis
DealShare became a unicorn in 2022 and targeted the rural and low-income groups. Based on a networking model for customer acquisition and a hyperlocal supply chain model, DealShare is increasing its customer base at a rapid pace. However, profitability was still a challenge, and converting high volume into high value continued to be a daunting task. This case study delves deep into the challenges co-founder Sourjyendu Medda and the DealShare team faced. It seeks to address key issues: how should DealShare leverage customer network for faster customer acquisition and how should they increase ticket size and profitability? As a data-driven business, what advantages does DealShare have in influencing customers’ buying behaviour using data? Dependence on social media could have a cascading effect on “word of mouth”. How can they manage customer complaints and increase engagement?
Complexity academic level
This case study has the potential to be used in different settings. In strategic cost management, this case study can demonstrate strategies for cost management in the value-conscious segment. This case study can be used in marketing management courses while teaching “positioning” in business-to-consumer markets and CRM. For second-year management students, this can be used in entrepreneurship and strategic management courses to demonstrate the network effect in social e-commerce start-up businesses. This case study is also relevant for various course modules in graduate management programmes to demonstrate the power of data-driven decision-making in business.
Supplementary materials
Teaching notes are available for educators only.
Subject code
CSS 8: Marketing
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Zhaoyang Sun, Haiyang Zhou, Tianchen Yang, Kun Wang and Yubo Hou
The shape of a product plays a crucial role in shaping consumer behavior. Despite the voluminous research on factors influencing consumers’ shape preferences, there remains a…
Abstract
Purpose
The shape of a product plays a crucial role in shaping consumer behavior. Despite the voluminous research on factors influencing consumers’ shape preferences, there remains a limited understanding of how the busy mindset, a mentality increasingly emphasized by marketing campaigns, works. This study aims to fill this gap by exploring the relationship between a busy mindset and the preference for angular-shaped versus circular-shaped products and brand logos.
Design/methodology/approach
This research consists of seven experimental studies using various shape stimuli, distinct manipulations of busy mindset, different assessments of shape preference and samples drawn from multiple countries.
Findings
The findings reveal that a busy mindset leads to a preference for angular shapes over circular ones by amplifying the need for uniqueness. In addition, these effects are attenuated when products are scarce.
Originality/value
This research represents one of the pioneering efforts to study the role of a busy mindset on consumers’ aesthetic preferences. Beyond yielding insights for practitioners into visual marketing, this research contributes to the theories on the busy mindset and shape preference.
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This paper aims to give an overview of the history and evolution of commercial search engines. It traces the development of search engines from their early days to their current…
Abstract
Purpose
This paper aims to give an overview of the history and evolution of commercial search engines. It traces the development of search engines from their early days to their current form as complex technology-powered systems that offer a wide range of features and services.
Design/methodology/approach
In recent years, advancements in artificial intelligence (AI) technology have led to the development of AI-powered chat services. This study explores official announcements and releases of three major search engines, Google, Bing and Baidu, of AI-powered chat services.
Findings
Three major players in the search engine market, Google, Microsoft and Baidu started to integrate AI chat into their search results. Google has released Bard, later upgraded to Gemini, a LaMDA-powered conversational AI service. Microsoft has launched Bing Chat, renamed later to Copilot, a GPT-powered by OpenAI search engine. The largest search engine in China, Baidu, released a similar service called Ernie. There are also new AI-based search engines, which are briefly described.
Originality/value
This paper discusses the strengths and weaknesses of the traditional – algorithmic powered search engines and modern search with generative AI support, and the possibilities of merging them into one service. This study stresses the types of inquiries provided to search engines, users’ habits of using search engines and the technological advantage of search engine infrastructure.
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Nirodha Fernando, Kasun Dilshan T.A. and Hexin (Johnson) Zhang
The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial…
Abstract
Purpose
The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.
Design/methodology/approach
The construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.
Findings
An ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.
Originality/value
The research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries.
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