The role of machine learning analytics and metrics in retailing research

This research presents the use of machine learning analytics and metrics in the retailing context. We first discuss what is machine learning and explain the field’s origins. We then demonstrate the strengths of machine learning methods using an online retailing dataset, noting key areas of divergence from the traditional explanatory approach to data analysis. We then provide a review of the current state of machine learning in top-level retailing and marketing research, integrating ideas for future research and showcasing potential applications for practitioners. We propose that the explanatory and machine learning approaches need not be mutually exclusive. Particularly, we discuss four key areas in the general scientific research process that can benefit from machine learning: data exploration/theory building, variable creation, estimation, and predicting an outcome metric. Due to the customer-facing nature of retailing, we anticipate several challenges researchers and practitioners might face in the adoption and implementation of machine learning, such as ethical prediction and customer privacy issues. Overall, our belief is that machine learning can enhance customer experience and, accordingly, we advance opportunities for future research.     

Exploring phygital omnichannel luxury retailing for immersive customer experience: The role of rapport and social engagement

Omnichannel retailing has revolutionized the way retailers create strategies for engaging customers in making purchase decisions. Phygital is a new-age transformative form of omnichannel retailing that emphasizes combining the physical and digital elements, with a particular focus on the human touch to satisfy social and symbolic consumer needs. Extant research has not fully addressed the role of phygital in luxury fashion retail. We explore the research question regarding how human interactions with experienced salespeople add value to the phygital experience. In doing so, we contribute to the luxury marketing literature by addressing the research gap by elucidating the role of phygital functionality in enhancing rapport building, social engagement, and developing trust and commitment, which results in a seamless customer experience, along with enhanced loyalty and patronage. Through 18 in-depth qualitative research interviews conducted with luxury retail managers and senior retail leaders, we provide guidelines to managers and practitioners at retail firms, to create actionable growth-oriented strategies focused on leveraging phygital capabilities.     

Managerial approaches towards service quality: the case of three service organisations

Using a multiple case study, this paper is concerned with assessing the impact of senior management's approach and attitudes on service quality and its implications for middle and firstline managers. Date from 52 semi-structured interviews representing a variety of managerial levels suggests that there exist many conflicts and differences in senior management's orientation and approach towards quality management (QM) with that of middle and firstline managers. The results further indicate that getting such consistency appropriate to the needs of top, middle, and firstline management, and of the QM itself, is one of the key problems of current management of service quality. However, the findings highlight that where there is consistency between senior managers' underlying approaches towards service quality goal with that of middle and firstline managers, service quality programmes will highly likely produce expected results. Finally, the implications of these findings as well as future research are put forward.     

Innovations in Retail Business Models

A retail business model articulates how a retailer creates value for its customers and appropriates value from the markets. Innovations in business models are increasingly critical for building sustainable advantage in a marketplace defined by unrelenting change, escalating customer expectations, and intense competition. Drawing from extant strategy and retailing research, we propose that innovations in retail business models are best viewed as changes in three design components: (1) the way in which the activities are organized, (2) the type of activities that are executed, and (3) the level of participation of the actors engaged in performing those activities. We propose six major ways in which retailers could innovate their business models to enhance value creation and appropriation beyond the levels afforded by traditional approaches to retailing. We also describe the drivers of business model innovations, the potential consequences of such innovations, and numerous examples from retail practice that highlight our concepts and arguments. In doing so, we provide a starting point for academic research in a domain that is deficient in theoretical and empirical research, and offer retailing managers a framework to guide retail business model innovations for sustainable competitive advantage.     

Customer-Based Valuation

Customer lifetime value (CLV) has emerged as an important metric to manage and grow customers. Marketing scholars have written many books and articles on this topic. However, most of this research has focused on tactical marketing decisions. While this is important, it is not enough to gain attention of senior managers who are concerned about firm level metrics such as stock price. To have greater impact marketing needs to go beyond brand-level profits to show the impact of marketing actions on firm profitability. In this paper we focus on customer lifetime value and its link to firm value. We discuss research that provides customer-based valuation of firms and suggest directions for future research.     

Understanding the user satisfaction and loyalty of customer service chatbots

The artificial intelligence (AI) chatbot is emerging as a significant corporate customer-facing application, potentially increasin customer service efficiency while reducing costs. However, little work has sought to assess the quality of service they provide consumers. This study applies the e-service quality by incorporating conversational AI quality to predict users' satisfaction and loyalty to customer service chatbots. The proposed model was empirically evaluated using survey data collected from 219 users responding about their perceptions of customer service chatbots. The findings indicate that AI chatbot service recovery quality and AI chatbot conversational quality significantly influence user satisfaction. On the other hand, core AI chatbot service quality and satisfaction significantly influenced chatbot user loyalty. This study contributes to researchers and practitioners by proposing and evaluating a more comprehensive chatbot e-service quality that combines both fundamental (core service and service recovery qualities) and human-like (conversational quality) aspects of e-service. The results are of value in devising future AI chatbot services and related strategies.     

The value of food waste: An exploratory study on retailing

Retailers are increasingly concerned with the sustainability of their business. Food waste is a major sustainability issue: 90 million tons of food are wasted in the EU every year. The production of much of this waste is directly linked to the food chain operations, included those performed at the retail stage. The literature on food waste has mainly focused so far on the quantification of the total food lost along the supply chain. However, the stage of retail has long been neglected. This paper attempts to partly fill this research gap, with the aim of measuring the extent of food waste in retailing as well as its environmental, social and economic value. To do so, we analyse the results of a food waste recovery project held in an Italian supermarket and, by drawing on the data collected in this case study, we perform an evaluation of the value of the food wasted. The results show that the extent of food waste in retailing is certainly considerable, both in terms of quantity and economic value. Moreover, we found evidence that it may be greatly reduced, with a significant limitation of its environmental impact and, through the mechanism of recovery, it may even generate social benefits. Despite the many limitations of such preliminary research, the results provide useful information for retailers aiming to develop strategies against food waste in the context of improving the sustainability of their business.     

Artificial Intelligence and Marketing: Pitfalls and Opportunities

This article discusses the pitfalls and opportunities of AI in marketing through the lenses of knowledge creation and knowledge transfer. First, we discuss the notion of “higher-order learning” that distinguishes AI applications from traditional modeling approaches, and while focusing on recent advances in deep neural networks, we cover its underlying methodologies (multilayer perceptron, convolutional, and recurrent neural networks) and learning paradigms (supervised, unsupervised, and reinforcement learning). Second, we discuss the technological pitfalls and dangers marketing managers need to be aware of when implementing AI in their organizations, including the concepts of badly defined objective functions, unsafe or unrealistic learning environments, biased AI, explainable AI, and controllable AI. Third, AI will have a deep impact on predictive tasks that can be automated and require little explainability, we predict that AI will fall short of its promises in many marketing domains if we do not solve the challenges of tacit knowledge transfer between AI models and marketing organizations.     

Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential

Artificial intelligence (AI) and machine learning (ML) may save money and improve the efficiency of business processes, but these technologies can also destroy business value, sometimes with grave consequences. The inability to identify and manage that risk can lead some managers to delay the adoption of these technologies and thus prevent them from realizing their potential. This article proposes a new framework by which to map the components of an AI solution and to identify and manage the value-destruction potential of AI and ML for businesses. We show how the defining characteristics of AI and ML can threaten the integrity of the AI system’s inputs, processes, and outcomes. We then draw from the concepts of value-creation content and value-creation process to show how these risks may hinder value creation or even result in value destruction. Finally, we illustrate the application of our framework with an example of the deployment of an AI-powered chatbot in customer service, and we discuss how to remedy the problems that arise.     

Innovation analytics: Leveraging artificial intelligence in the innovation process

Artificial intelligence (AI) is about imbuing machines with a kind of intelligence that is mainly attributed to humans. Extant literature—coupled with our experiences as practitioners—suggests that while AI may not be ready to completely take over highly creative tasks within the innovation process, it shows promise as a significant support to innovation managers. In this article, we broadly refer to the derivation of computer-enabled, data-driven insights, models, and visualizations within the innovation process as innovation analytics. AI can play a key role in the innovation process by driving multiple aspects of innovation analytics. We present four different case studies of AI in action based on our previous work in the field. We highlight benefits and limitations of using AI in innovation and conclude with strategic implications and additional resources for innovation managers.     

Emerging Market Retail: Transitioning from a Product-Centric to a Customer-Centric Approach

In an environment with digital disruptions, retailers must adopt a customer-centric approach to survive and compete effectively. Retailers need to be agile and forward-looking in adopting the relevant analytics and performance metrics to bring a customer-centric approach across upstream and downstream activities in the retail value chain. However, retailers in emerging markets (EMs) need clarity on the specific analytics and performance metrics in the value chain that will enable them to transition from their current product-centric state to the desired customer-centric state. Employing a triangulation approach (i.e., literature review, marketplace evidence, and managerial interviews) in the fragmented retail landscape of EMs, this study provides an organizing framework that explains: (i) the need for a customer-centric approach across the retail value chain, (ii) the specific performance metrics that need to be adopted across upstream and downstream activities in the retail value chain to enable EM retailers to achieve their desired customer-centric state, and (iii) the role of analytics in providing insights to achieve these performance metrics and improving monetary and non-monetary firm performance outcomes. We also provide firm-specific and macro-level conditions that can influence the EM retailers’ adoption of relevant analytics and explain the different paths retail formats can follow to adopt analytics. We present a strategy matrix that enables retail managers to identify the appropriate analytics to be adopted at different retail value chain stages to achieve desired performance metrics. We also highlight future research opportunities in retailing in EMs.     

An E-Valuation Framework for Developing Net-Enabled Business Metrics Through Functionality Interaction

Managers engaged in net-enabled business planning seek metrics to help them analyze the success of their e-business investments. Likewise, researchers require metrics to build analytical models and conduct empirical research on the impact of e-business strategies on firm performance. In this article, the authors develop a comprehensive E-Valuation Framework for identifying net-enabled applications and their resulting user-based functionalities for activities across the value chain. The authors propose that the real value from net-enabled applications can be found in functionality interactions, where one application enables or enhances functionality in another application. The comprehensive framework can be used to generate three types of metrics managers can use to evaluate their net-enabled strategic initiatives. Further, a classification of net-enabled organizations provides the basis for selecting applications critical to a firm's strategic thrusts. We make use of the resource-based view of the firm and real-options analysis to discuss how successful application deployment is based on the resources and assets the firm possesses as well as managing the rollout of an applications portfolio over time. The framework allows managers to map their organization's net-enabled initiatives into a coherent, easily understood visual representation and provides direction for researchers evaluating the efficacy of net-enabled business strategies.     

The Impact of Individual Ethics on Reactions to Potentially Invasive HR Practices

In recent years, the practices of work organizations have raised increasing concerns regarding individual privacy at work. It is clear that people expect and value privacy in their personal lives. However, the extent to which privacy perceptions influence individuals’ work attitudes is less clear. Research has explored the extent to which employee perceptions of privacy derive from characteristics of the programs themselves. However, there is a paucity of research that examines how the characteristics of the individual employee may influence perceptions of these programs. In this study we seek to shed light on this issue, as we examine how the individual ethical orientation of employees influences perceptions of a variety of human resource programs that have the potential to be perceived as invasive. Results indicate that ethical orientation exerts direct effects on perceived invasiveness of programs and exerts both direct and indirect effects on perceived appropriateness of programs. Implications for research and for managers adopting privacy-related programs are discussed.     

Service sabotage: The dark side of service dynamics

While many aspects of services research assume that employees are largely compliant to management prescribed service standards, a number of recent studies have highlighted the deliberate sabotage by service workers as a key issue. We contend that service sabotage is important not simply because of the pervasiveness of such behaviors, but also because of the impact that such acts can have on firm growth and profitability. Consequently, we seek to achieve three inter-linked objectives in this article. First, we highlight how service saboteurs harm customers’ service experiences and negatively affect the performance of the firm. Second, in order to assist managers in recognizing these behaviors, we identify the most common types of service saboteurs and forms of sabotage. Specifically, we classify and describe four main types of service saboteurs: Thrill Seekers, Apathetics, Customer Revengers, and Money Grabbers. Finally, and most importantly, we provide a series of suggestions regarding how managers might effectively address service sabotage in their firms. These include gathering information and exploiting existing data to establish the extent and nature of sabotage, recruiting the right quality of service staff, training and rewarding employees, enriching and empowering employees, developing a service culture, and initiating better monitoring systems and procedures.     

Allied Breweries and the Development of the Area Manager in British Brewing, 1950-1984

Brewing in the United Kingdom in the years following 1950 sawa shift from a production to a retailing orientation. As partof this shift, the role of the area manager started to movefrom production and sales discipline to retail development.This article explores the job of the area manager during theperiod, seeking to demonstrate the weakness in recent accountsthat suggest that area managers serve only as an "informationrelay" between senior managers and unit managers. Although theevidence is limited, because of problems with the survival ofrecords, it suggests a more complex picture, which has implicationsfor area managers in retail and service industries more generally.     

Barriers to ascension to senior management positions in retailing

Using a case study of retailing, this paper examines the continued under-representation of women in senior management positions. Via a questionnaire survey, it reveals that those factors retail managers (men and women) themselves attribute to the disproportionate number of women in senior positions. The findings revealed that the main factors were associated with women's ‘other’ role: the family. Thus, lack of child care facilities and high family commitments were regarded as especially problematic and the organisation of retailing with its long anti-social hours and lack of flexi-time at managerial levels contributed to these problems. Other factors were also regarded as important including company cultures that uphold patriarchal social systems. The paper demonstrates how women's primary position in the home and domestic domain and men's primary position in the economic domain have shaped the way retail organisations are organised and the roles that men and women are traditionally expected to adopt within them.     

World consumer lifestyles databook

A case is made that the adoption of IT in European retailing is inhearntly conservative and is not characterized by the rapid revolutionary change sometimes argued to be the case. Reasons are suggested for the slow rate of integration of IT into retail management process and the limited range of applications in use operationally. These reasons are considered as within the nature of IT and within the culture of retailing. The impact of IT in retailing is considered in respect of cost reduction, improved asset productivity, changing internal relationships and the changing external relationships of retailers. Some areas of potential research are listed.     

Retailing and retailing research in the age of big data analytics

As a research domain, the retail sector has always had many appealing features, such as its size, its multi-faceted and dynamic nature, the possibility for researchers to exploit their own domain knowledge, and an extensive coverage by business analysts. In addition, the above-average availability of good-quality data has historically been an additional selling point to empirical researchers. The paper considers to what extent the latter still holds, and explores a number of additional opportunities and challenges that emerge from the ongoing big data revolution. This is done from five perspectives: retail managers, retailing researchers, public-policy makers, investors, and retailing educators.     

An Evaluation of the Effectiveness of Internet Advertising Tools

ABSTRACT

This study explores a wide variety of Internet advertising tools. It presents an assessment of the persuasive impact of Internet advertising tools based on the perceptions of senior executives at interactive advertising agencies. The persuasion matrix developed by McGuire (1978) is used as a framework for assessing the impact of Internet advertising tools on the response hierarchy of consumers. Based on this assessment, a series of research propositions are offered in the spirit of propositional inventories for future testing. Finally, included is a discussion that alerts managers to important issues involved in using Internet advertising tools.