Many retailers and food service providers offer programs as part of their loyalty programs in which customers are given stamps for each purchase of a qualifying product or service and redeemed for a reward once a certain number of stamps have been accumulated. We identify which stimuli in such goal-directed motivational promotions induce customers to participate in the program.

The popularity of live streaming is driving the emergence of a new business model, known as live-streaming commerce (LSC). While there are more and more broadcasters in LSC, their behaviors and performance of them are significantly different. To have a better understanding of broadcasters, we employ different machine learning models to identify different portraits in both static and dynamic dimensions. We collect a rich live-streaming dataset from one leading platform in China. Our dataset features information for both broadcasters and viewers, including viewers’ purchasing behaviors, viewers’ records of posting words, broadcasters’ gender, the number of followers for broadcasters, and the live streaming show information, including the start and end time, and the viewers in each live streaming show. The rich textual information in broadcasters’ profile induction provides us a good opportunity to uncover different static portraits and the records in live streaming shows give us a chance to identify different dynamic behavioral portraits for broadcasters.

The popularity of live streaming is driving the emergence of a new business model, known as live-streaming commerce (LSC). Consumers spend more and more time on smartphones, and the emerging business model of live-streaming commerce (LSC) is flourishing in the retail industry. With highly interactive features, LSC social interactions influence viewer purchase behaviors. To examine the interactions between influencers and viewers, we collected a rich dataset from a leading LSC service platform and integrated research models from the natural language process (NLP) field and econometric models.

The application of mindfulness is increasing significantly in different areas of business studies. However, identifying how mindfulness research has evolved and the major research themes, specifically within the business studies domain, remains lacking. This study unveils the intellectual structure of mindfulness research in business studies. Using citation and co-citation analysis, the study identifies the most influential articles, annual growth, and three key research clusters constituting the intellectual foundation.

Frontline employees (hereinafter FLEs) act as boundary spanners, primary representatives, and intermediaries between consumers and service organizations. They are often directly responsible for service delivery and are the customers’ first impression of service organizations. Therefore, maximizing FLE performance is vital for service organizations. Leaders have been argued to play a critical role in fostering FLE performance for a variety of reasons, one of which is to achieve goal-related results. To achieve those results, they often feel a pressing need to discipline their subordinates’ actions. Consequently, leaders may take corrective measures that display controlling behaviors to press subordinates’ best performance. This type of leadership style is known as Authoritarian Leadership (hereinafter AL), which refers to leaders with paternal attributes who utilize absolute authority and control over their subordinates with the expectation of unquestionable obedience. The literature, however, has reported mixed findings of the performance benefits of AL.

This study tests the influence of multi-visual dimensions and textual features of electronic word-of-mouth (EWOM) on its perceived helpfulness on a sample from Saudi Arabia. This investigation is conducted in the context of Twitter through an online factorial experiment. The design incorporates a 3 (visual inclusion to text: with product-only photo, with product and face photo, without product photo) × 3 (EWOM valence: positive, positive and negative, and negative) between-subjects experiment (n = 540). It is concluded that when evaluating EWOM helpfulness, pictures do in fact contribute substantial value. For females, this effect is more pronounced when the EWOM is two-sided at the product-only photo level, and when EWOM is negative at the product with a face photo level. Thus, this study adds to the body of existing theories by arguing that EWOM helpfulness largely depends on how the textual and visual features of EWOM are communicated.

Anthropomorphism is a prevalent marketing practice that fosters consumer perceptions of a brand as humanlike. In today’s hyperconnected marketplace, firms are increasingly imbuing their brands with human features with the hope that the favorable perceptions of humanlike attributes in nonhuman objects could lead to consumers’ positive evaluation of humanized products. For example, Amazon has imbued Echo, a voice-activated Bluetooth speaker, with the human name Alexa, a female voiced virtual assistant that employs familiar human speech pattern, and some advanced personality traits. Similarly, Hormel Foods has used Mr. Peanut, the advertising logo and mascot of Planters that embodies the brands’ selling points. Mr. Peanut is depicted as a humanized peanut with arms, legs, top hat, and monocle and became a vessel of brand meaning and personality, taking on the product quality that the brand aims to communicate. Prior studies that use brand anthropomorphism as a foundation have investigated the impact of brand anthropomorphism on various outcomes such as product evaluations, emotional responses, and intentions to replace a product. However, what is missing from prior work is an understanding of the impact of brand anthropomorphism on the purchase intentions for clearance products which are sold under a retailer’s promotional strategy as an inventory management tool. The lure of cheapened goods may expand the range of consumers who can afford to buy merchandise from the company or may provide existing customers with an appealing purchasing option. In light of this, clearance sales are known to be effective not only for increasing store traffic by alluring price-conscious consumers but also for reducing excess inventory in a retail location or a chain of product fulfillment. The strategic importance of clearance sales has increased since the breakdown of COVID-19 which forced retailers to close their stores and caused demand for many product categories to plunge in early 2020. After the initial shock of the pandemic, consumer spending recovered fairly quickly, giving rise to record levels later in the same year. This surprising recovery continued into the next year as consumer sentiment and spending levels surged together, resulting in consumer demand that surpassed retailers’ stock levels. However, due to inflation and amounting fears of recession, consumer spending started to slow down again in 2022, resulting in the opposite of what happened in the previous year. Such a reversal caused many retailers to face high inventory levels and declining profitability, forcing them to cut prices to move excess inventory out of stores, which increases the importance of conducting clearance sales effectively. Clearance sales are prevalent in retail markets, where considerable discounts are typically offered for leftover items (Zhang & Cooper, 2008). Retailers widely use clearance sales to liquidate their unsold products at the end of a selling season (Nocke & Peitz, 2007). They have strong incentives to get rid of the remaining items in order to make room for the new products (Sällström, 2001). Previous research suggests that anthropomorphism leads consumers to apply human schema to a product, which in turn affects their attitude toward the product (Aggarwal & McGill, 2007, 2012). In this research, we aim to identify the negative effect of anthropomorphism on consumers’ attitude toward clearance products.

In addition to humanoid and robotic designs, an increasing number of AI-powered services are being represented by non-human species (i.e., zoonotic design). Yet, little is known about the consequential effects of such zoonotic AI on consumer adoption of these services. Drawing on the concept of speciesism and Cognitive Load Theory, the current research seeks to uncover how does using zoonotic (vs. robotic) designs affects consumer adoption.

A consumer psychologist observes someone make a choice between chocolate cake and fruit salad, a classic measure of self-control (Shiv & Fedorikhin, 1999). Since the cake is relatively tastier but unhealthier (i.e., a vice; Wertenbroch, 1998), a choice of cake is interpreted as a lack of self-control, whereas a choice of fruit salad (a virtue) is viewed as successful self-control. The simplicity and intuitive appeal of this heuristic has led it to be widely adopted by consumer psychologists. However, a comprehensive understanding of the operation of self-control requires food consumption to be analyzed as a two-stage process: choice followed by intake quantity (Wansink & Chandon, 2014). Self-control processes may be relevant to both stages of a decision of what to eat (choice stage) and a decision of how much to eat the chosen option (quantity stage)—they may influence both choice and quantity. Examining the role of self-control in terms of post-choice quantity control is critical since over-consumption of calories is the single most significant contributor to obesity (Livingston & Zylke, 2012). The overconsumption problem is not an exclusive matter of vice foods. Eating virtuous foods can result in excessive calorie intake and thus consumers need to control the intake of virtues as well as vices.

The proliferation of service robots has led to a growing concern about the impact of these technological advancements on privacy. Despite the development, quantitative research on the influence mechanism of privacy concerns on service robot adoption intentions is still limited. This research explores the influencing mechanism and boundary conditions of the interaction effect between customer privacy concerns and service type on customers’ service robot adoption intentions.

The wide application of digital media technology in fashion shows has become the epitome of the development and innovation of today's fashion industry, enabling designers to break through the constraints of time and space, changing the performance of today's fashion shows, and making them present unprecedented new features. With the development of information technology, the integration of emerging digital technology and the fashion industry is accelerating. So far, separate studies have been carried out in various academic fields on the combination of Metaverse and NFT, but the current status and nature of relevant research are still incomplete. Furthermore, the current research on virtual fashion shows and NFT in China's apparel industry is limited. The purpose of this study is to investigate the influence of digital fashion marketing stimulation on consumer brand attitudes using the stimulation-organ-response (SOR) framework model. By analyzing 77 cases of virtual fashion shows in China, this study obtained antecedent variables and designed a research model. An online sample of 300 Chinese Gen Z consumers was collected and analyzed using SPSS and FSQCA. This research hopes to provide valuable information for the sustainable development of China's fashion industry, and to help Chinese fashion brands confirm the future market development direction of Metaverse and NFT.

With the expanding availability of market data, firms are increasingly reliant on analytical capabilities as a source of competitive advantage, a trend that is reflected in the rising budgets allocated to data and analytics (The CMO Survey, 2022). Analytical capabilities denote firms' capacity to define and extract insights from the available data and link these insights to decision-making (e.g., Cao et al., 2019; Penttinen & Frösén, 2022). Despite the growing influence of the capability perspective on marketing analytics, which is rooted in the resource-based view (Barney, 1991), the understanding of analytical capabilities as a source of performance disparities remains in its early stages. In particular, although analytical capabilities of firms constitute (1) capabilities internal to the firm, as well as (2) those shared within the firm’s broader business network, the vast majority of previous research focuses on the development and use of internal analytical capabilities only (Gupta & George, 2016; Wedel & Kannan, 2016). As a result, there remains limited understanding regarding shared analytical capabilities that assume close collaboration between business partners, such as suppliers, buyers, and third parties, in developing and sharing data and insights (Alinaghian & Razmdoost, 2018; Penttinen & Frösén, 2022) and extend beyond the boundaries of individual firms.

There are a lot of brand experience in Metaverse. For example, we can participate in Samsung Galaxy Fan party, UC Berkeley graduation class, and even Ralph Lauren store in Metaverse. When the consumers experience such events in Metaverse, they have to use their avatar by making a user name. They have the option of using either their real or fictional name in Metaverse. There are two types of avatar in Metaverse. First, they can use actual self-avatar by using their real name. Second, they can create totally new avatars using made up name. The name is one of the symbols of self. Therefore, we can easily predict that consumer experience with avatar will affect the consumer perception differently. Which type of avatar will then enhance the brand engagement? Results show that the consumer experience with avatars affected brand attitudes differently. Also, the consumer's experience with avatars based on their actual images in the Metaverse affected the positive brand attitude. This study suggests that Metaverse avatars can also let people interact with themselves and with each other in parasocial ways. This study examines the role of avatar in virtual world; consumers experience with avatar can provide useful implications in terms of digital transformation.

Expressing political stances is not rare among service providers such as taxi drivers and chefs. For instance, in 2021, a restaurant owner angry at the death of U.S. soldiers during the evacuation of Afghanistan posted a sign on the front door telling Biden supporters to eat elsewhere (Miller 2021). Given findings from research on brand activism, consumers can be expected to have less favorable attitudes toward service providers who are more politically different from them. However, if service providers who are politically opposite are more competent than ones who are politically identical, would consumers still choose politically identical but less competent service providers? To our knowledge, no research has been conducted to examine what factors influence consumers’ choices between more competent but politically opposite service providers and less competent but politically identical service providers. To fill that gap, in our research, we examined the role of consumers’ political ideology (i.e., conservative vs. liberal) in making trade-offs between more competent but politically opposite service providers and less competent but politically identical ones.

This research addresses financial market communication of marketing information (i.e., information related to firms’ organic growth opportunities) through depth interviews (Study 1) and quantitative data on conference calls and stock market reactions (Study 2). The investigation (1) reveals that marketing, despite high potential relevance for financial markets, often plays only a marginal role in firms’ financial market communication and (2) develops a framework for effectively communicating marketing to financial markets.

With the development of WEB 3.0 and the metaverse, the emergence of chat GPT, and AI is attracting attention across all industries. AI technologies such as robotics, advanced analytics, and in-store applications created a sensation in the fashion industry, as well as created an exceptional customer experience. In this study, fashion AI types (e.g. AI models: generative, conversational, AI applications: design, production, sales, retail, marketing) and case analysis (e.g. concepts, characteristics, benefits, risks) are examined. Consumer experiences with fashion AI are also discussed for future research directions. Finally, the Fashion AI research framework and research agenda are discussed for future research.

Customer value co-creation behavior (CVCB) has been regarded as a strong predictor of firm performance in many industries for decades. CVCB—the customer’s direct and indirect contribution of resources to enhance the offering of the focal agent/object—is ubiquitous in service industries. Recently, customer engagement has been identified as a determinant of the value realized by customers and businesses. Customer psychological engagement (CPEngagement) is a multidimensional customer-firm relationship marked by customer satisfaction and emotional connectedness to the firm. Although there is concurrence that customer engagement and CVCB are linked, scholars diverge as to the precise nature of the relationship. Marketing and hospitality literature have not yet developed an integrated model of customer engagement with the digital and physical components of hospitality services. Given the increasing managerial interest in digital customer engagement and value co-creation behaviors, it is essential to enhance our understanding of the interplay between these concepts and their implications for both consumers and businesses. This research investigates the relationship between CPEngagement and value co-creation in the digital and physical aspects of hospitality services.

This study explores the role of the digital communication in determining customers’ e-service agent use behavior and examines whether perceived communicator authority interacts with communication style toward strengthening or weakening future e-service agent use intention. The results of this study provide pioneering evidence on the effects of digital service communication strategies. This study contributes to digital service research by exploring the communication strategies of e-service agents. Results also provide implications for practitioners on how to achieve most out of deploying digital communications in the digital customer service platform.

Metaverse provides technology for people to connect, find communities, and grow businesses. Its sales have seen growth during the COVID-19 pandemic. In an era of metaverse, luxury brands such as Gucci, Ralph Lauren, Burberry, Balenciaga, and Dolce & Gabbana are trying to adapt to new changes. They launched NFT(Non-fungible token) goods, digital fashion, and virtual luxury goods on various metaverse platforms such as Zepeto, Roblox, and Fortnite. For example, Ralph Lauren in Zepeto provides various types of luxury items, immerses in virtual performances, and has a game plot interaction. As people immerse themselves in the Metaverse, they feel happy from various activities—such as watching advertisements, drinking juice, and playing with friends. Thus, what factors should be considered when the luxury brands manage the metaverse?

The unbounded nature of digital innovation requires innovating firms to be agile in the way they manage the processes, governance and outcomes in order to sense and seize the market directly and timely. This study adopts an inter-organizational approach and asks to what extent and in what way does organizational agility impact on innovation performance? This perspective underscores the interdependencies between collaborating partners, which creates a relationship regulating system of workflow to drive value creation in the process of innovation. While the literature has offered a broad conceptual argument for organizational agility in the context of digital innovation, the mechanisms through which value is transformed in the innovation process is still unclear. We contend that an agile innovation process stands on four main cornerstones: (1) joint strategic planning, (2) joint problem solving, (3) joint improvisation and (4) community (market) sensing. The empirical research is set in the video game industry, which is in a largely digitalized and borderless business environment. The data was collected through an interviewer-administered questionnaire. The sampling frame is based on a Swedish trade association database. Usable sample is 113. We performed structural equation modelling to test the hypothesized model, including main and moderation effects, using Mplus. The findings show that while only improvisation has a significantly positive effect on innovation performance, the role of strategic planning and problem solving between two collaborating partners remains unclear. For example, strategic planning has shown to be a negative influence in our empirical research. Problem solving has no effect on innovation performance, but it interacts with community sensing and subsequently facilitates innovation outcome. This highlights the importance of community sensing, which could offer rich, crucial knowledge and resources for problem solving that proves to be effective. The results provide further theoretical arguments for understanding organizational agility and digital innovation, but also raise further questions for future research.