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Journal of Targeting Measurement and Analysis for Marketing
Number of Followers: 1  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0967-3237 - ISSN (Online) 1479-1862
Published by Springer-Verlag Homepage  [2349 journals]
  • Analyzing the analytics: data privacy concerns
    • Authors: Maria Petrescu; Anjala S. Krishen
      Pages: 41 - 43
      PubDate: 2018-06-01
      DOI: 10.1057/s41270-018-0034-x
      Issue No: Vol. 6, No. 2 (2018)
       
  • Analyzing ecology of Internet marketing in small- and medium-sized
           enterprises (SMEs) with unsupervised-learning algorithm
    • Authors: Hon Keung Yau; Ho Yi Horace Tang
      Pages: 53 - 61
      Abstract: Internet marketing is a business imperative due to the irrevocable and unstoppable trend of Internet. In this paper, we propose the methodology of unsupervised learning algorithm to apply on the survey data of Internet marketing. Hidden relationships among critical factors in the model are examined using PC-algorithm. To analyze the ecology of Internet marketing in small-and-medium enterprises, similar commercial organizations are grouped into segments by K-means clustering for studying their characteristics. The last methodology is to perform two levels of clustering using self-organizing map and K-means algorithm to save computational cost for massive data instances. The analytical result describes the overview of the Internet usage under stiff-competition business environment which is beneficial to management level to make a more appropriate decision to upload the existing marketing activities online.
      PubDate: 2018-06-01
      DOI: 10.1057/s41270-018-0030-1
      Issue No: Vol. 6, No. 2 (2018)
       
  • A novel method for detecting careless respondents in survey data:
           floodlight detection of careless respondents
    • Authors: Volkan Dogan
      Abstract: The current paper proposes a novel method for detecting careless respondents, namely, floodlight detection of careless respondents. This novel method consists of two steps: (1) creating a nonsense regression model and (2) testing a moderator role of response time on the nonsense regression model. An illustration of the floodlight detection of careless respondents method was performed with online survey data collected from 341 Turkish participants. The floodlight detection of careless respondents method is the first systematic approach to calculate a cut-off value for response time, which distinguishes careless respondents from careful respondents. According to the results of floodlight detection of careless respondents, the percentage of careless respondents was 59.8%, which is little higher than the percentage of careless respondents calculated through Instructional Manipulation Check (40.7%) and bogus item (44.2%). The floodlight detection of careless respondents method is described herein, and implications are provided for future research.
      PubDate: 2018-05-23
      DOI: 10.1057/s41270-018-0035-9
       
  • Online relationship marketing for banks in face-to-face economies
    • Authors: Muhammed S. Alnsour
      Abstract: Online relationship marketing enables organisations to maintain and develop relationships with new and existing customers. In this study, we investigate online relationship marketing and the resulting loyalty for banks and their customers in an economy where face-to-face interactions are the norm. We introduce a model comprising relationship interaction and relationship quality and validate this for Jordanian banks and their SME customers. Increases in relational interaction were found to have a positive effect on the relationship quality dimensions of trust, satisfaction, and commitment. These then led to an increase in customer loyalty. Despite the preference in the economy for social presence in retail interactions, banks were able to establish effective online retail relationships with their SME customers.
      PubDate: 2018-05-02
      DOI: 10.1057/s41270-018-0032-z
       
  • Who searches where' A new car buyer study
    • Authors: Yashar Dehdashti; Brian T. Ratchford; Aidin Namin
      Abstract: In this research, we address an important gap in the literature as to the search behavior of new car buyers. While the effect of the Internet on this process is known, the literature still lacks a comprehensive study which (1) concurrently covers time periods before and after the launch of the Internet, and (2) compares trends of consumer search across those combined years. Our unique survey dataset, which spans 22 years and includes consumer search information for new cars from both the pre- and post-Internet eras, enables us to investigate this important gap. Using a latent class model, we classify respondents according to variables that measure consumer search for new automobiles. We unveil changes in characteristics of the six latent segments of car shoppers. Our main findings show that, over the years since the advent of the Internet, the segment of car buyers who mainly search through car dealers/stores has been shrinking drastically. We also find evidence that, over time, the heavy Internet user segment has become less likely to have decided on the manufacturer/dealer prior to searching. Our findings benefit researchers, practitioners, car manufacturers, dealers, and buyers.
      PubDate: 2018-04-16
      DOI: 10.1057/s41270-018-0033-y
       
  • User-level incremental conversion ranking without A/B testing
    • Authors: Zhuli Xie; Yong Liu
      Abstract: The traditional approach to build incremental conversion prediction model has to rely on A/B test results. However, under certain intense business environment, A/B testing can be limited by technical support, platform, or budget, and become not practically available. In this paper, we propose an algorithm to rank users by incremental conversions resulted from advertising effects, which is based on user’s conversion history and the output from a conversion prediction model. By appropriately defining who an active user is, this algorithm is proven to work well with real data. In case where an A/B test is not available and incremental conversion-based user targeting is desired, this algorithm offers a practical solution.
      PubDate: 2018-03-28
      DOI: 10.1057/s41270-018-0031-0
       
  • Analytics from our scholarly closets: the connections between data,
           information, and knowledge
    • Authors: Anjala S. Krishen; Maria Petrescu
      PubDate: 2018-02-19
      DOI: 10.1057/s41270-018-0029-7
       
  • Loss or gain' The impact of Chinese local celebrity endorser scandal
           on the global market value of the endorsed brands
    • Authors: Junzhou Zhang; Lei Huang
      Abstract: Can a local celebrity endorser event influence the endorsed global brand’s stock value' Employing cultural perspective, signal theory and attribution theory, we hypothesized that, in an emerging market such as China, the endorsed global brands could gain and brands endorsed by a low-blameworthy celebrity could gain more from a local celebrity endorser scandal event. Using event study method, our results suggest that the entire endorsed brand portfolio exhibits statistically significant gains on the global stock market shortly after the focal scandal event, and brand portfolio endorsed by low-blameworthiness celebrity accrued more gains than brand portfolio endorsed by high-blameworthiness celebrity. The discussion of managerial and policy implications is presented in the concluding section.
      PubDate: 2018-02-19
      DOI: 10.1057/s41270-018-0028-8
       
  • Guidelines for assessing the value of a predictive algorithm: a case study
    • Authors: Ossi Ylijoki
      Abstract: Predictive algorithms are increasingly used to support decision making. Understanding the costs and benefits of a predictive model is an important aspect for businesses. However, algorithms are abstract, and their impact oftentimes remains vague. We present a case study, where a machine-learning algorithm is used for bid qualification. We show how to apply classification matrices for business value assessment and propose guidelines and metrics for interpreting the impact in practical solutions.
      PubDate: 2018-01-15
      DOI: 10.1057/s41270-017-0027-1
       
  • Analyzing customer satisfaction in self-service technology adopted in
           airport
    • Authors: Hon Keung Yau; Ho Yi Horace Tang
      Abstract: Customer satisfaction level is one of key performance indicators in the service industry. The various factors affecting this are studied to maintain an excellent relationship with customers. Self-service technology (SST) is widely implemented by companies in service sector. This paper proposes to apply the customer satisfaction survey to investigate factors influencing the customer satisfaction. The relationships among the factors are discovered using PC-algorithm. The critical factors are identified to be inputs in regression tree and ANN to estimate the customer satisfaction level. By means of comparison of models, importance of selected inputs is quantified and discussed. The results show that customer satisfaction has strong connectivity relationship with personal service attributes as well as affective and temporal commitment by running PC-algorithm. ANN validated by 10-fold cross validation is the best among the models. The most important factor influencing the satisfaction level to the companies is the customer’s desire of continuing a relationship. The key benefit of the proposed approach is to avoid making subjective decisions, for instance, building a plausible initial path models in the analysis. The analytical results facilitate the decision-making process and better resource allocation in the airline and state its future development of self-service technology.
      PubDate: 2018-01-11
      DOI: 10.1057/s41270-017-0026-2
       
  • Are brand benefits perceived differently in less developed economies'
           A scale development and validation
    • Authors: Samy Belaid; Selima Ben Mrad; Jérôme Lacoeuilhe; Maria Petrescu
      Pages: 111 - 120
      Abstract: The purpose of this paper is to develop a scale measuring consumers’ brand benefits in less developed economies. Based on the literature, items have been generated in qualitative and quantitative studies and tested by using exploratory and confirmatory factor analyses. The findings show that brand benefits converge into a two-factor structure (functional and symbolic) instead of three (functional, experiential and symbolic). These findings can be justified by the fact that consumers in developing economies do not have as much experience with brands as the ones from developed economies. The results also relate to previous literature findings on the topic of utilitarian and affective brand relationships. This scale can be used to advance the domain of brand benefits in a cross-cultural environment and can be employed by marketers when businesses plan to brand their products in developed economies.
      PubDate: 2017-12-01
      DOI: 10.1057/s41270-017-0024-4
      Issue No: Vol. 5, No. 3-4 (2017)
       
  • Declining transportation funding and need for analytical solutions:
           dynamics and control of VMT tax
    • Authors: Pratik Verma; Shaurya Agarwal; Pushkin Kachroo; Anjala Krishen
      Pages: 131 - 140
      Abstract: There is a growing concern among policy makers and analysts regarding the mismatch between demand and supply of the revenue for improving and maintaining highway infrastructure. One possible solution is to link actual vehicle miles traveled (VMT) to the fee structure. The main objective of this paper is to model VMT dynamics and establish a methodology for designing an optimal VMT tax rate. The paper proposes a novel model for VMT dynamics and estimates the model parameters using historical data. An optimal control problem is then formulated by designing a cost function which aims to maximize the generated revenue while keeping the tax rate at a reasonable rate. Using optimal control theory, a solution is provided to this problem. Steady-state analysis of this model is provided and simulations are performed for the 50-year period showing the projected VMT, generated revenue, and the optimal tax rate. The model provides a parameter in the cost function which can be adjusted for achieving a certain amount of revenue in a given time frame.
      PubDate: 2017-12-01
      DOI: 10.1057/s41270-017-0025-3
      Issue No: Vol. 5, No. 3-4 (2017)
       
  • Marketing analytics: from practice to academia
    • Authors: Maria Petrescu; Anjala S. Krishen
      Pages: 45 - 46
      PubDate: 2017-06-01
      DOI: 10.1057/s41270-017-0019-1
      Issue No: Vol. 5, No. 2 (2017)
       
  • Marketing intelligence and customer relationships: empirical evidence from
           Jordanian banks
    • Authors: Ghazi A. Al-Weshah
      Abstract: This study aims at investigating the role of marketing intelligence in maintaining and building customer’s relationships in Jordanian banks. More specifically, to measure the effect of marketing intelligence on maintaining and building current and new customer’s relationships. The quantitative design has been built in the study methodology such as descriptive and hypothesis testing methods. A self-administrated questionnaire has been developed as data generation instrument. Using the convenient sample, 110 questionnaires were distributed to executives of marketing, customer relationships, information systems, and customer services who work in Jordanian banks' headquarters. Only 85 questionnaires were returned with response rate 77%. The study concludes that there is significant positive effect for MI on maintaining and building both current and new customer relationships. However, MI practices in Jordanian banks tend to get a new customer rather than to retain an existing one. Moreover, Jordanian banks have potentials to upgrade their marketing intelligence systems in order to achieve competitive advantages based on customer relationship approach. The study provides important lessons in applying marketing intelligence in maintaining and building customer relationships for practitioners or executives in banking industry.
      PubDate: 2017-11-08
      DOI: 10.1057/s41270-017-0021-7
       
  • Exploring the key drivers behind the adoption of mobile banking services
    • Authors: Tahir M. Nisar; Guru Prabhakar
      Abstract: This research examines the main drivers behind the adoption of mobile banking, a concept that has revolutionized the day-to-day activities of humans. A review of relevant literature on the topic, leads us toward testing the following key hypotheses: consumers are adopting mobile banking due to the perceived usefulness and benefits associated with the concept; and consumers are adopting mobile banking due to technological advances meaning increased access to the mobile phone devices. We published an online questionnaire on Amazon Mechanical Turk to obtain responses from Internet users. A dominating proportion of participants highlighted how mobile banking is a concept that they adopted between three and 5 years ago, showing just how recently mobile banking took off. The results also showed a number of links between the study’s research hypotheses and the adoption of mobile banking. The overall result of the study shows online banking as a concept that is influenced by a number of both internal and external factors. No single factor plays a dominating force in pushing retail bankers to adopt mobile banking, with it instead being a culmination of numerous different factors. The recent introduction of mobile banking is made seemingly apparent, as is the increasing susceptibility to change in the near future. Subsequently, countless opportunities for further academic research are likely to arise.
      PubDate: 2017-11-07
      DOI: 10.1057/s41270-017-0023-5
       
  • Statistical perceptual maps: using confidence region ellipses to enhance
           the interpretations of brand positions in multidimensional scaling
    • Authors: Dawn Iacobucci; Doug Grisaffe; Wayne DeSarbo
      Abstract: Positioning is among a marketer’s preeminent strategic responsibilities. Positioning helps to clarify brand strengths among competitors and identify potential challenges of similar brands and possible substitutability. Assessments of positioning, from initial marketplace efforts to resources directed at modifications and re-positioning, are frequently assisted by the graphical representations of brands in multidimensional space. Such perceptual maps are constructed to reflect the closeness of brands and therefore the extent to which they are seen as interchangeable, versus distances between brands representing their relative positioning distinctiveness. To create perceptual maps, data are frequently obtained that comprise a sample of respondents rating a series of brands with respect to their perceived similarities and differences, as well as the status of each brand along multiple attributes. This research uses the variability inherent in such three-dimensional data to construct confidence regions around point estimates in perceptual maps. Current maps tend to be simply descriptive, with positions reflected by point estimates, but multivariate models including multidimensional scaling and multi-mode factor analysis can be modified to extract the subject heterogeneity and derive inferential perceptual maps. Confidence regions that overlap will indicate more clearly an inference of brand similarity, whereas non-overlapping regions imply statistically differentiated brand perceptions.
      PubDate: 2017-11-02
      DOI: 10.1057/s41270-017-0022-6
       
  • Measuring media channel performance: a proposed alternative to the
           ‘last-in wins’ methodology
    • Authors: Gary S. Robertshaw
      Abstract: Advertising effectiveness has traditionally been measured by recording the medium through which a response is precipitated. Though other channels may have contributed to the precipitation of a response, the media channel that precipitated the response is often considered the solitary contributor to that response—the so-called ‘last-in wins’ methodology. Although this methodology has been used to avoid double- or triple-counting responses, it ignores the contribution of those media channels that are not attributed with the response but which nevertheless provably assist in delivering the final, precipitated response. In addition, the ‘last-in wins’ methodology fails to incorporate media synergy, whereby the strategic linking of media channels can produce a greater overall benefit than the sum of its parts. The current study expands upon the findings of previous studies in this field, for example, Naik and Raman (J Mark Res 40:375–388, 2003) and Schultz et al. (J Direct Data Digital Mark Pract 8:13–29, 2012), by proposing an alternative method of measuring media channel performance; one which quantitatively incorporates media synergy. The proposed alternative method is applied in an online environment using case studies from the insurance and education sectors. It reveals significant differences compared to extant media measurement approaches, whilst considering the implications for media planning and synergistic response attribution.
      PubDate: 2017-09-25
      DOI: 10.1057/s41270-017-0020-8
       
  • Segmentation of the senior market: how do different variable sets
           discriminate between senior segments'
    • Authors: Yamen Koubaa; Rym Srarfi Tabbane; Manel Hamouda
      Abstract: Senior consumers represent an important portion of the market, and as such, they require an appropriate segmentation to explore the consumption characteristics of the different segments composing this specific market. The present study focuses on how different variable sets impact senior consumers’ segmentation. We apply Wedel and Kmakura segmentation framework and Hagerty’s formulation to assess quantitatively the classification power of many variable sets in terms of six segmentation criteria namely identifiability, responsiveness, substantiality, actionability, accessibility, and stability. Findings from a survey conducted over 427 senior consumers show that the variable sets have different supports for each of the above criteria indicating that some sets should be privileged over others in senior consumers’ segmentation. The paper reports the details of this investigation and provides implications for managerial practice and academic research on senior market segmentation.
      PubDate: 2017-07-12
      DOI: 10.1057/s41270-017-0017-3
       
  • Constructing brand value proposition statements: a systematic literature
           review
    • Authors: Deborah Goldring
      Abstract: This study examines the state of communicating the brand value proposition via a systematic literature review from research published in marketing journals from 1996 to 2015. A sample of 56 articles from high-quality marketing journals examines the components of the brand value proposition statement, applicable theories, and descriptive findings. There has been an increased interest in the research on brand value propositions as value creation becomes more customer-focused and value-based selling becomes more pervasive. This exploratory study suggests an ongoing need for examining the effectiveness of types of brand value propositions in terms of both the managerial process in which they are constructed as well as the precision of such brand promises on customer understanding. The paper concludes with a suggestion for more robust empirical research on the construction and deconstruction of brand value propositions, a need for more managerially focused research, and a future research that examines the under-researched area of how value propositions are effectively communicated on branded websites.
      PubDate: 2017-04-13
      DOI: 10.1057/s41270-017-0014-6
       
  • Uncovering the paths to helpful reviews using fuzzy-set qualitative
           comparative analysis
    • Authors: Shimi Naurin Ahmad
      Abstract: Researchers have found evidence that helpful product reviews written by other consumers have the potential to alter consumers’ purchase decision and influence overall sales. In the quest to find what makes a review helpful, prior studies have documented volume, valence, argument quality, and source certainty as determinants of helpful reviews. However, these studies used regression analysis and found significant effects of each of the determinants regardless of other variables. Taking a different perspective, the present study uncovers the “causal recipe” (combination of antecedent conditions) of helpfulness review by applying a fuzzy-set qualitative comparative analysis. Congruent with elaboration likelihood model, this study finds that high argument quality and high source certainty, together in a review, do not make a review helpful, and consumers use heuristics (peripheral cues) when reading a long review. Negative as well as long reviews are found to be helpful. Real consumer reviews collected from Amazon.com are used for this study. The study contributes to the literature by uncovering different paths (path signifies configuration of variables) that lead to helpful reviews by using a fs-QCA technique on real Amazon.com reviews and attends to the call of using sophisticated techniques in exploring new online data.
      PubDate: 2017-04-12
      DOI: 10.1057/s41270-017-0015-5
       
 
 
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