Search results

Online web searches have played crucial roles in influencing consumers’ purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning.

This study builds upon the interesting observation that consumers’ behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers’ minds over time.

Results show that consumers’ web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers’ simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers’ behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers’ behavior of searching simultaneously for a specific brand and certain product attributes.

Theoretically, this study verifies that consumers’ web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.

Companies spend millions on training their sales representatives. Thousands of textbooks have been published; thousands of training videos have been recorded. Hundreds of good pieces of advice and tips for sales representatives have been presented along with hundreds of sales methods and techniques. Probably the largest number of indicators and measures are applied in sales and distribution. On the one hand, this is a result of the fact that sales provide revenue and profit to a company; on the other hand, the concept of management by objectives turns out to be most effective in regional sales teams with reference to sales representatives and methods of performance evaluation. As a result, a whole array of indices has been created which enable the evaluation of sales representatives’ work and make it possible to manage goods distribution in a better way.

The indices presented in this chapter are rooted in the consumer market and are applied most often to this type of market (particularly in relation to fast-moving consumer goods at the level of retail trade). Nevertheless, many of them can be used on other markets (services, means of production) and at other trade levels (wholesale).

Although the values of many indices presented herein are usually calculated by market research agencies and delivered to companies in the form of synthetic results, we have placed the emphasis on the ability to determine them independently, both in descriptive and exemplifying terms. We consider it important to understand the genesis of indices and build the ability to interpret them on that basis. What is significant is that the indices can be interpreted differently; the same index may provide a different assessment of a product’s, brand or company’s position in the market depending on the parameters taken into account. Therefore, we strive to show a certain way of thinking rather than give ready-made recipes and cite ‘proven’ principles. Sales and distribution are dynamic phenomena, and limiting them within the framework of ‘one proper’ interpretation would be an intellectual abuse.

In the retailing industry, database is the time and place where a retail transaction is completed. E-business processes are increasingly adopting databases that can obtain in-depth customers and sales knowledge with the big data analysis. The specific big data analysis on a database system allows a retailer designing and implementing business process management (BPM) to maximize profits, minimize costs and satisfy customers on a business model. Thus, the research of big data analysis on the BPM in the retailing is a critical issue. The paper aims to discuss this issue.

This paper develops a database, ER model, and uses cluster analysis, C&R tree and the a priori algorithm as approaches to illustrate big data analysis/data mining results for generating business intelligence and process management, which then obtain customer knowledge from the case firm’s database system.

Big data analysis/data mining results such as customer profiles, product/brand display classifications and product/brand sales associations can be used to propose alternatives to the case firm for store layout and bundling sales business process and management development.

This research paper is an example to develop the BPM of database model and big data/data mining based on insights from big data analysis applications for store layout and bundling sales in the retailing industry.

The purpose of this paper is to offer a perspective of brand-based analysis on green brand positioning differentiation through a network analysis approach.

This study employs centrality and distinctiveness as bases to develop a matrix framework of green brand positioning differentiation. The two dimensions are measured from the techniques of network analysis, including analysis of the core-periphery structure and adjacency matrix.

The results yield four clusters with different positions in a 2×2 matrix, including 23 core brands with high-positioning distinctiveness, ten core brands with low-positioning distinctiveness, ten peripheral brands with high-positioning distinctiveness, and seven peripheral brands with low-positioning distinctiveness.

The results contribute to providing brand researchers with different analytical perspectives on the existing knowledge about green brand positioning and offer strategic positioning information for green brand practitioners.

This research contributes to the literature in three ways. First, this research is a first attempt to offer a brand-based perspective on differentiation of green brand positioning. Second, this research advances the existing knowledge that uses network analysis on green brand positioning by offering different techniques for brand differentiation analysis. Finally, this research complements the strategic positioning information of the current business environment in the context of green branding.

With the advent of fierce international competition in today's industrial business environment, it has become imperative for companies to reevaluate the cost/price/value relationship of their products. In particular, highly competitive products require much closer attention to and control of the cost/price/value relationship to ensure continuing profitability. This paper examines one such product in an actual industrial setting (pseudonyms have been used to maintain data confidentiality) using a rather comprehensive conceptual framework based on Market Structure Analysis concepts. The proposed framework basically represents the industrial buying decision process which is both multiattribute and multiagent in nature. As pointed out by Sheth (1973) and Choffray and Lilien (1980), these industrial decision processes tend to become extremely complex due to heterogeneity among decision makers.

This paper aims to analyze the relative importance of brand‐packaging, price and taste in the formation of brand preference for manufacturer and store brands in food product categories.

The authors first perform a blind taste test of the product using three brands (two manufacturer brands and one store brand) in two categories with differentiated characteristics (cola drinks and olives stuffed with anchovies). They then use conjoint analysis to analyze the influence of the intrinsic cue (taste) and the extrinsic cues (price and brand‐packaging) on consumers' preference for manufacturer and store brands. Finally, after telling the consumers which taste belongs to each brand, the authors study the influence of the extrinsic cues on the consumers' quality evaluations of the real stimuli.

The results show that not knowing the brand to which the taste tested belongs, leads consumers in general to order their preferences fundamentally by taste. However, the results differ by product category and consumer segment analyzed. Consumers who evaluate the taste of store brands as better change their preferences more when they know which brand belongs to which taste. Further, the change in preference when consumers know the brand‐taste correspondence is clearly greater in the most differentiated category.

The main limitations of this research derive from the factors conditioning the information. A greater number of categories and attributes would enrich the information. In addition, it would be useful to analyze more than one store brand.

The results obtained have interesting implications for manufacturers and retailers concerning management of the brands in their product portfolio and management of their relationships in the distribution channel.

The main contribution of this paper lies in the work methodology used. The paper offers a comprehensive analysis of how the relative importance of brand‐packaging, price and taste affect brand preference for manufacturer and store brands. The study also contributes evidence on how the consumer's knowledge of the correspondence between brand and taste can change his or her brand preferences, an issue of great interest for manufacturers and distributors in managing their product portfolios.

In the past 25 years, employer and internal branding have grown significantly. Prior reviews tended to focus on either one of these domains. This study aims to map the intellectual structure of research on both employer branding and internal branding, thereby identifying impactful authors and journals, current and evolving themes and avenues for future research.

Using VOSviewer and Biblioshiny software packages, a bibliometric analysis of 739 articles was conducted using various methods such as citation analysis, bibliographic coupling, cluster analysis, keyword analysis and three-field plot. The Scopus results were further validated using 297 articles produced by the Web of Science data set. It ensured the robustness of the results and generalizability of the findings across bibliometric data sets.

The findings first report the impactful articles, authors and institutions of employer and internal branding research, along with popular keywords used in this area. Next, the analysis reveals four major clusters and seven subthemes (i.e. employer brand and job seekers, employer brand and employees, employer brand and international human resource management (HRM), third-party employer branding, internal branding – conceptualization/review, internal branding – antecedents and consequences, internal brand management). Early research focused more on “corporate brandings,” whereas current research deals more with “employer branding: antecedents and consequences,” “employer branding conceptualization/review,” and “internal branding” and its subthemes. The employer and internal branding clusters have evolved largely independent from each other. This study offers future research directions and practical implications per cluster.

To the best of the authors’ knowledge, this study is the first comprehensive bibliometric analysis of both employer and internal branding research.

This study aims to draw on cue utilization and irradiation theories to: determine the extent to which country-of-origin image and its sub-dimensions exert an aggregate and relative influence on consumer brand evaluations; and identify the contextual and methodological factors that account for between-study variance in the focal relationship.

A random-effects model was used to examine 166 empirical articles encompassing 499,563 observations, and 282 effect sizes from 1984 to 2020 using Comprehensive Meta-Analysis software.

Results show that country-of-origin image has a positive, moderate effect on consumer brand evaluations. Moreover, findings reveal that each dimension of country-of-origin image – general country image, general product country image, specific product country image and partitioned country image – significantly influences consumer brand evaluation, but the effect of general product country image is the largest. What’s more, the aggregate impacts of country-of-origin image on consumer brand evaluation – brand commitment, brand-specific associations and general brand impressions – show that the effect on brand commitment is the largest. Finally, findings show that contextual factors (brand source, product sector, culture [individualism vs collectivism], brand origin continents and respondents’ continent) and methodological factors (cues, sampling unit, publication year and sample size) significantly account for between-study variance.

This study provides the first meta-analytic review of the relationship between country-of-origin image and consumer brand evaluation to help clarify mixed findings and balance out the literature, which has only seen quantitative reviews on product evaluation and purchase decisions.

This paper focuses on the role of manufacturer brands for resellers within retail channels. This topic is important because of the strategic value of manufacturer brands and the increasing influence of resellers within channels of distribution. Much of the branding research emphasizes a customer-brand knowledge perspective; however, emerging perspectives suggest that brands are also relevant to other stakeholders including resellers. In contrast, channels research recognizes the manufacturer sources of market power, but does not consider the impact of manufacturer “push and pull” strategies within channels. Existing theoretical frameworks, therefore, do not address the reseller perspective of the brand. As a result, the research approach is a multi-method design, consisting of two phases. The first phase involves in-depth interviews, allowing the development of a conceptual framework. In the second phase, a survey of supermarket buyers on brands in several product categories tests this framework. Structural equation modeling analyzes the survey responses and tests the hypotheses. The structural model shows very good fit to the data with good construct validity, reliability, and stability. The findings show that manufacturer support, brand equity, and customer demand reflect the manufacturer brand benefits to resellers. A key contribution of this research is the development of a validated scale on manufacturer brand benefits from the point of view of a reseller. This research shows that the resources that relate to the brand, not just the brand name itself, create value for resellers in channel relationships.