Journal of Marketing Analytics最新文献

Accommodation services are perceived by consumers as possessing a greater purchase risk compared to goods, especially in first-purchase situations and during international travel. To mitigate this risk, consumer prospects look for cues that indicate the quality of service they can expect. This research investigates the role of social relationships in consumer purchase decision-making within rapidly growing accommodation sector of the sharing economy. Utilizing Airbnb’s social connection feature, consumers can see how they are socially connected with Airbnb hosts worldwide. We employ a censored proportional hazard model on a sample of 4,316 consumer prospects who have used social connection feature at least once. Additionally, we re-estimate the model using a propensity score matched sample of 8,632 consumers. The study reveals a positive association between the use of social connection feature and the hazard rate. Specifically, findings indicate that the using social connection feature for searching for accommodation reduces the time to make a first purchase. The article discusses the managerial implications of these findings.

The aim of this paper is to study the impact of sustainable practices and relational innovation on guests’ perception of value co-creation and brand equity. Moreover, the existence of differences in the proposed relationships is analyzed by employing hotel size as a moderator. A sample of 391 hotel guests was collected utilizing a structured questionnaire. The relationships between the variables were examined using structural equation modeling. The results revealed the boosting effect of sustainable practices and relational innovation on value co-creation. In addition, it can be observed how value co-creation and brand equity enhance guests’ response to revisit intention.

Companies engage in philanthropic corporate social responsibility (CSR) activities not only to genuinely support certain organizations and people but also to promote and improve brand recognition and image. CSR activities target the environment, sports, and arts and culture. However, surprisingly, few studies have explored all of these and demonstrate their effectiveness in core businesses. This study investigated the impact of CSR activities on the perceived value of products and advertising in the Japanese and American markets. The target brands were Coca-Cola, McDonald’s, Nestle, and Starbucks. We collected online surveys from 754 people in the two countries and applied structural equation modeling. Environmental and sports activities positively affected core business factors, whereas arts and cultural activities had a negative effect. Increasing environmental awareness and sports interest could lead to the observed positive effects. Companies make art-related investments to receive tax breaks, and art and cultural activities are limited to society’s elite, which could have led to the negative effects observed. This study provides valuable insight for the food industry to formulate strategies for allocating limited internal financial and human resources to CSR activities.

Predictive modeling aims at providing estimates of an unknown variable, the target, from a set of known ones, the input. The k Nearest Neighbors (kNN) is one of the best-known predictive algorithms due to its simplicity and well behavior. However, this class of models has some drawbacks, such as the non-robustness to the existence of irrelevant input features or the need to transform qualitative variables into dummies, with the corresponding loss of information for ordinal ones. In this work, a kNN regression variant, easily adaptable for classification purposes, is suggested. The proposal allows dealing with all types of input variables while embedding feature selection in a simple and efficient manner, reducing the tuning phase. More precisely, making use of the weighted Gower distance, we develop a powerful tool to cope with these inconveniences. Finally, to boost the tool predictive power, a second weighting scheme is added to the neighbors. The proposed method is applied to a collection of 20 data sets, different in size, data type, and distribution of the target variable. Moreover, the results are compared with the previously proposed kNN variants, showing its supremacy, particularly when the weighting scheme is based on non-linear association measures.

Against the backdrop of the resource-based theory (RBT), this research paper aims to analyze if different types of analytics personnel exist in the context of Big Data Marketing Analytics (BDMA) and to profile the discovered personnel clusters. The study adopted the survey method to collect data in Canada and the United States among the marketing personnel working in firms with at least limited experience in the deployment of BD. The collected data were analyzed with ANOVA and a two-step cluster analysis procedure. The cluster variate included technical, technology management, business/marketing, and relational knowledge constructs with their relevant indicator variables. The profiling of the clusters was also completed. The findings indicate the existence of two sufficiently large clusters among the marketing personnel. They had very different profiles regarding their gender, decision-making role, BD deployment level in their respective firms, and experience level. This research sheds light on the types of marketing analytics personnel required to implement BDMA successfully. The personnel active in BDMA deployment must have relevant experience in technical, technology management, business/marketing, and relational knowledge and possess higher decision-making abilities, which enables their firms to proceed successfully to more advanced levels of BDMA deployment.

Abstract

This concise review delves into the dynamic intersection of globalization and information and communication technology (ICT) in education, where economic, technological, and cultural forces converge with the widespread adoption of digital tools. Globalization standardizes education worldwide, emphasizing preparation for the global economy and fostering an interconnectedness of educational systems. Simultaneously, ICT revolutionizes education, enhancing student engagement, motivation, and performance while necessitating adaptability from educators. Identified gaps in the literature underscore the need for emphasis on educators' perspectives, in-depth exploration of pedagogical changes, attention to training and professional development, comparative studies, examination of equity and inclusion, exploration of counseling, and guidance for educators. Proposed recommendations advocate for active engagement in continuous professional development (CPD), seamless ICT integration, addressing the digital divide, nurturing twenty-first century skills, prioritizing student-centered learning, fostering mental health, and embracing learning analytics. Future research directions advocate for investigating the impact of emerging technologies, addressing digital equity, assessing the effectiveness of online and blended learning, exploring teacher training, evaluating student outcomes through learning analytics, and investigating global perspectives and parental involvement. These endeavors aim to provide evidence-based insights, shaping the future of education in an increasingly digital world, with a specific emphasis on the transformative potential of learning analytics.

Abstract

There are two approaches to treating marketing expenditures, not as a cost to be expensed, but as an investment in a financial asset. The customer equity (CE) approach views customer relationships as generating future returns and uses customer lifetime value (CLV) models. The brand equity approach (BE) views brands as creating future returns and uses measures of the financial value of brand (FVB). Although some CE research has introduced brands as one driver of CLV, the two approaches diverge in important ways. This paper identifies key differences between them and proposes two ways the CE and BE perspectives could be integrated into a common approach. One way is to distinguish between brand relationships and calculative relationships in building CLV models. Another is to triangulate measures of FVB with CLV measures.

Based on the involvement literature, the current research redefines the involvement theory and proposes a new form of involvement, namely situated involvement. The research, then, develops a scale to measure this involvement employing a mixed methods procedure. Afterward, the relationships between enduring, response, and situated involvements as well as the memorability of experience are investigated using structural equation modeling (SEM). The results from a survey of 317 tourists in Queenstown, New Zealand show that the memorability of experience is only impacted by situated involvement, the type of involvement which occurs during an experience. Enduring and response involvements are found to influence situated involvement, and enduring involvement predicts response involvement.

In the context of multi-sided platform (MSP) literature, the strategic use of first-party content is well established. In these contexts, consumers’ value perceptions of first- and third-party content is assumed to be equivalent. In the marketing literature, however, it is generally accepted that the perceived value of products from store brands is significantly lower than products from manufacturer brands. This study investigates whether the same difference exists among consumers on a multi-sided platform. The study finds that consumers perceive products sold by the platform as delivering significantly less value than substitutes from third-party brands, and that this difference persists independently of price. The implications of the findings for managers and marketers are that (i) first-party content strategies on MSPs are limited by consumers’ value perceptions. This implies that (ii) managers should calibrate their first-party content strategies according to target customers’ preferences and that (iii) in their analytics, marketers should distinguish between first- and third-party content.

The current digital landscape is evolving at an increasingly rapid pace where “data is the new oil” of the global economy. Like oil, extracting value from raw data is a complex process as it is not useful in its raw state. As data continue to be generated and relied upon, data literacy skills are becoming increasingly critical. Since data must be ‘prepared’ prior to its analysis, this paper highlights three core competencies—cleaning, transforming, merging (i.e., data preparation)—that are required to build a sound marketing analytics foundation. Expanding data literacy to include the ability to transform data from its raw state into a usable form will enhance students’ overall level of proficiency and marketability in marketing analytics. It is imperative to include the teaching of data preparation as part of the analytics curriculum in marketing analytics courses to ensure that students attain the greater level of data literacy. Data preparation assignments that will help students enhance their marketing analytics skillset, and increase their overall knowledge and marketability are included.