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We study whether and how the availability of incremental time associated with retirement and unemployment affects the types of products households buy. For this, we develop a new theoretical model of the composition and size of the grocery shopping basket subject to money and time constraints. We construct a novel household panel data set that combines purchase records for grocery goods with information on labor market status and other demographics. We use the data to document that, in line with predictions from the model, consumers buy more varieties and generally shift their spending into products that take more time to turn them into consumption experiences. This paper was accepted by Eric Anderson, marketing. Funding: B. J. Bronnenberg and Y. Xu acknowledge financial support from the Netherlands Foundation for Scientific Research (NWO) under a Vici grant. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2023.4763. [ABSTRACT FROM AUTHOR]

This research aims to examine the impact of cultural values and technology of e-commerce on consumer purchase behavior in Brunei Darussalam. In Brunei, the practice of Melayu Islam Beraja (MIB) has regulated all commercial activities and implementation of strict laws in the advertisement code. However, in comparison to its surrounding nations, Brunei is unable to overcome the cultural gap, despite the fact that they all have conservative societies. Marketing and commercial activity numbers in Brunei are quite low as there are fewer e-commerce platforms in Brunei compared to its neighboring countries (Lazada and Shopee). As there is a slow development of technology, this impacts consumer purchasing behavior and economic development in the country. The primary obstacle to perceived usefulness in Brunei is the cost of internet connectivity. Internet access in Brunei is highly costly, especially when using social media. The research philosophy employed in this study is pragmatism and the research method used is Quantitative. The results of the study verified the significance of these factors and the culture in Brunei and consumer purchasing behavior. The findings revealed that consumers' purchase behavior is mainly influenced by meaning transfer and perceived value factors. Trustworthiness and attractiveness do not influence the relationship for the study as culture reduces consumer confidence in their purchasing behavior. Furthermore, technology does not moderate the relationship between the variables and consumer purchasing behavior. Consumers frequently face challenges in their purchasing journeys due to a lack of access to cutting-edge technology. This study aims to empower businesses by strategically leveraging Social Media Influencers (SMIs), which will improve sales performance and marketing management strategies. Furthermore, it aims to provide companies with the tools they need to broaden their expertise, refine both technical and soft skills, and bridge any knowledge gaps in marketing and communication management. This study recognizes and addresses a couple of limitations. One potential limitation of employing a survey methodology for quantitative research, particularly with a sample size of 384 respondents, is the possibility of encountering methodological constraints. [ABSTRACT FROM AUTHOR]

In Malaysia, meal delivery systems have proliferated after the COVID-19 outbreak. There is a growing trend among consumers to transition from purchasing food in-store at restaurants to placing orders online via food applications. Notwithstanding the surge in digital food sales, internet consumers continue to desire the tactile encounter offered by eateries. The transition from dining in restaurants to purchasing food online presents considerable challenges for food companies attempting to comprehend consumer behaviour about online food purchases. Thus, the effect of sensory cues on online food purchases is investigated in this study. Furthermore, this study explores the association between online food consumption and sensory cues, in addition to investigating the relationship between consumer behaviour and demographic variables such as age, gender, income, and employment status. A quantitative survey of 359 online food purchasers from the Klang Valley was undertaken. SPSS was employed to perform an empirical analysis of the correlations that were identified. Analysis using linear regression revealed that sensory cues impact the purchasing decisions of consumers. Additionally, age and wealth were found to have an impact on consumer purchasing behaviour, but gender and employment were found to have a negative influence. The insights derived from these studies have the potential to aid food producers in the formulation of effective marketing strategies that are tailored to individual customer profiles and sensory preferences. As a result, this could enable them to meet the evolving needs of online food consumers. [ABSTRACT FROM AUTHOR]

Social network platforms as ubiquitous media in our today lives are the venue of many everyday activities including purchasing products and services. This study set out to explore key strategic factors of online consumer purchase behavior in social network platforms. ISM methodology is used for comparing the variables that are extracted from the Delphi technique and confirmed by the experts. To collect the data, a questionnaire was developed and distributed among a limited sample of experts in microeconomics, social networks marketing and consumer purchase behavior to compare twelve factors. The findings revealed that 'Consumer engagement', 'Consumer's value perception' and 'Perceived risk' are placed at the level I. Thus, they would be positioned at the top of the ISM model. Meanwhile, findings show that 'Trust', 'Social influence', 'Social support' and 'Value co-creation' are the most important strategic variables of research. Thereafter, all linkage variables are strategic variables. This, in terms of MICMAC analysis, means such variables are significant and are worth the investment in the future based on the cross-impact analysis. The results of this study can be used for platform businesses to deepen the user engagement level and to lead the customers to purchase decision. Also future researchers can use the findings of this research to propose new models of user engagement in social network platforms or to investigate the relationship among the identified factors. [ABSTRACT FROM AUTHOR]

Information on short-term rental platforms plays an important role in consumer purchase behavior. However, information asymmetry between host and guest has been identified as a problem in sharing economy contexts. In this paper, to fill this gap, the authors develop six hypotheses about the focal impacts of self-presentation strategy and the moderating effects of third-party certification. Based on data from Airbnb, the authors first examine how the tactics of self-presentation strategy influence consumer purchase behavior. The results show that different self-presentation tactics affect consumer purchase behavior differently. The authors also found that the third-party certification level weakens the influence of self-presentation strategy interactions on consumer purchase behavior. [ABSTRACT FROM AUTHOR]

Storytelling can arouse consumers' emotions and affect purchasing behavior through desires and attitudes. While the marketing literature discusses storytelling, there is a lack of consensus because of the diverse conceptual and operational definitions used. To untangle the complexities and consolidate the fragmented knowledge about storytelling in marketing, this research examines how the marketing literature has addressed the influence of storytelling on consumers' purchasing behavior. The findings aid in understanding how the topic has been discussed from a marketing perspective in consumer behavior studies. Through a systematic literature review using a bibliometric analysis, we demonstrate that the marketing literature features four strands about the uses of storytelling to influence consumers' purchasing behavior. First, storytelling stimulates the consumer's identification with the brand. Second, storytelling allows consumers to experience emotional value. Third, storytelling supports engagement behaviors. Finally, storytelling has a downside in that it also propagates harmful speech. This study concludes with a roadmap for future research about how storytelling impacts consumers' purchasing behavior. [ABSTRACT FROM AUTHOR]

Celebrity endorsements is a popular form of marketing whereby companies hire well known celebrities to promote their products. Big scale celebrity endorsements entice endorsement fees in millions of dollars. However, there exists limited literature discussing this theme of celebrity endorsements for the Indian footwear industry. The said industry has been growing at a rapid rate and is witnessing involvement of celebrity endorsements at a large scale. Therefore, this study has tried to perform an empirical analysis which can be used by Indian footwear industry for strategizing their celebrity endorsements campaigns. It was found that the Indian footwear industry is unable to make profitable gains from the amount that it invests in the celebrity endorsements. This result was measured considering that the footwear industry hires a celebrity based upon his / her attractiveness and credibility. However, attractiveness of the celebrity has no significant contribution in enticing consumer interests or consumer purchase of the footwear product. It has been suggested that Indian footwear companies need to carefully select a celebrity who can be suitably matched to the underlying product so as to maximize the efficiency of the celebrity endorsement campaign. [ABSTRACT FROM AUTHOR]

As the usage of e-commerce is growing rapidly, it is significant to analyze the features or attributes that influence the consumer purchase behavior in E-commerce. This study examines how the activities of a consumer will impact the consumer purchase behavior in e-commerce. This study presents a novel explainable causal variational autoencoders based equivariant graph neural network. The model combines the usage of causal modeling technique to identify the important causal relationships, variational autoencoders to learn the latent representations of data and equivariant graph neural networks to analyze the data to understand the factors which influence the E-commerce purchase behavior of consumers based on their activities. The datasets used in our research were gathered from open repositories. We propose a causal variational autoencoders based equivariant graph neural network to predict the e-commerce purchase behavior of consumers and apply an explainable artificial intelligence approach to visually explain the factors that influence the prediction. The proposed methodology is compared with the existing machine learning and deep learning methods. The proposed method outperforms other models by achieving mean squared error (MSE) as 4.49, mean absolute error (MAE) as 0.74, root mean squared error (RMSE) as 2.11, R-Squared (R 2) as 97.17 and mean absolute percentage error (MAPE) as 4.75 on Dataset_1 and MSE as 35.85, MAE as 0.036, RMSE as 5.98, R 2 as 92.29 and MAPE as 0.54 on Dataset_2. The proposed methodology demonstrates a 10.72% mean improvement in R 2 value for Dataset_1 and a 10.46% mean improvement in R 2 value for Dataset_2 compared to the state-of-the-art models. Based on the explainable artificial intelligence analysis, we observed that the features such as total number of purchases, the number of store purchases, and the number of web visits play a major role in predicting the e-commerce purchases. [ABSTRACT FROM AUTHOR]

Corporate Social Responsibility (CSR) has emerged globally as an important field of study as corporations increasingly recognize the positive consequences of ethical behavior in their business operations. However, despite a growing body of literature, results and definitions remain somewhat contradictory and fractured. Taking a marketing business ethics perspective, this article examines the influence of CSR in firms and its impact on consumer buying behavior through a systematic examination of state of the art literature over the past two decades (2000–2020). Our review identifies a theoretical connection between CSR initiatives and positive consumer reaction yet a lack of material relevance. Most publications have assumed linear and rational decision-making, and comparative studies addressing contextual factors e.g. culture are lacking. Following from this, our paper addresses the results and implications of CSR activities concerning these elements and creates a new framework through which consumer behavior can be analyzed. [ABSTRACT FROM AUTHOR]

This article mainly considers the coexistence of physical sales channels and online sales channels. Online retailers with online sales channels consider whether to provide return policies and whether to provide consumers with return insurance. The research established four return strategy models that: do not provide returns; provide returns but do not provide return insurance; provide return insurance, but the cost is borne by online retailers; and provide return insurance, but the cost is borne by consumers. The authors then studied the online retailers' optimal return and shipping insurance selection strategies. The results show that when the proportion of residual return value after the value reduction of unit returned products was large, online retailers set higher sales prices and provided return policies, while offline retailers needed to reduce sales prices in order to attract more consumers. When the consumer unit product return compensation was relatively large, online retailers chose to provide consumers with free return insurance; otherwise, it was more beneficial for online retailers not to provide return insurance. Further research found that although the cost of online retailers increased when freight insurance was taken, it could better attract consumers, which was more beneficial to online retailers. [ABSTRACT FROM AUTHOR]

The declared state of emergency and the measures taken against the spread of coronavirus by governments have increased Internet shopping. All companies, regardless of size and type of business activity, had to adapt their business models to the new circumstances through transformation of their business processes and offering products or services tailored to the changing customer behavior. This study aims to analyze the peculiarities of online sales during the COVID-19 health crisis via the integration of classic and modern data analysis methods. The purpose of the paper is to identify the main factors determining user behavior and examine their impact on customer satisfaction in e-commerce. The survey method and structural equation modeling (SEM) were used to recognize the dependencies between variables from the online users' perspective. The satisfaction determinants indicated and described in the paper affect differently the perceived value for the customers. As this value is subjective and dynamic, this study developed a reliable system for e-commerce factor evaluation. Using the proposed methodology, companies can constantly monitor and assess indicators influencing customer satisfaction and gain awareness of consumer behavior's dynamics in online shopping. e-commerce marketers can employ the obtained results to decide how to organize order execution and optimize supply chains. Identifying the most important components of the e-commerce value, managers of online retailers can better run online sales platforms, increase customer loyalty, and thus, improve company's online performance. [ABSTRACT FROM AUTHOR]

Customer churn is considered a critical issue for all businesses, as customer loss leads to a decrease in future profits. Although acquiring new customers can address such losses, this process tends to cost more than retaining existing customers. Therefore, identifying potential churners and then retaining them is important. While churn prediction has been studied widely, current research must analyze more complex business models in response to their increase, such as platform businesses. However, modeling churn prediction for these businesses is challenging because consumer behavior over platforms is more complicated. Past approaches to churn prediction can be improved upon using recent advancements in deep learning that capture the nonlinear relationships behind the data in a data-driven manner, especially for complex business models. This study proposes a method of extracting latent features from purchase histories as explanatory variables for churn prediction using a variational autoencoder with the actual customer distribution as a prior. The proposed method is validated using real purchase data from a platform business and shows a 1.5% improvement in F-measure against the baseline, and a 20% improvement for customers with recent transactions. Subsequently, the variables are examined using several methods for data analysis to interpret the meanings of the extracted features and underlying customers' purchasing behavior in the group of potential churners. With these analyses, the model provides practical implications for understanding what kind of purchasing behavior may lead to churn and planning effective retention strategies. [ABSTRACT FROM AUTHOR]

Given the mediating role of value co-creation, this paper tries to demonstrate how social network marketing (SNM) could influence consumer purchase behavior (CPB). The proposed hypotheses are empirically tested in this study using a PLS-SEM and Necessary Condition Analysis (NCA) method combination. The novel methodology adopted in this study includes the use of NCA, IPMA matrix, permutation test, CTA, and FIMIX. The assessment of the outer model, the inner model, the NCA matrix, and the IPMA matrix are the four steps that the paper takes. Instagram users with prior experience making purchases online made up the statistical population of the study. Four hundred twenty-seven questionnaires were analyzed by SmartPLS3 software. Based on the findings, SNM positively and significantly influenced economic, enjoyment, and relational values. Furthermore, these three types of values significantly and directly influenced CPB. For CPB, the model accounted for 73.8% of the variance. The model had high predictive power because it outperformed the PLS-SEM benchmark for all of the target construct's indicators in terms of root mean square error (RMSE). According to the NCA's findings, SNM, economic, recreational, and relational values are necessary conditions for CPB that are meaningful (d ≥ 0.1) and significant (p < 0.05). Four prerequisites must be met for CPB to reach a 50% level: relational value at no less than 8.3%, enjoyment value at no less than 16.7%, economic value at no less than 33.3%, and SNM at no less than 31.1%. The highest importance score for SNM is shown to be 0.738, which means that if Instagram channels improve their SNM performance by one unit point, their overall SNM will also improve by 0.738. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate and compare the popularity of common grocery apps in Hungary as well as Iran. The data were gathered from Iranian and Hungarian users who had at least one online purchase experience using a grocery app. A Gaussian mixture model (GMM) and multi-layer perceptron (MLP) are used as supervised and unsupervised machine learning algorithms with Python programming to cluster customers and predict consumer behavior. The results revealed that Wolt in Hungary and Snappfood in Iran are the most popular grocery apps. Users in Iran are divided into three groups of users of app services and the type of full covariance has higher accuracy compared to the other three types (96%). Meanwhile, we found that the five apps used in Hungary have provided 95% accuracy from the users' point of view based on the diagonal covariance. The MSE value (overfitting and cross-validation) is less than 0.1 in the MLP algorithm, which shows an acceptable amount of error. The results of overfitting indicate the proper fit of the MLP model. The findings of this study could be important for managers of online businesses. In the clustering section, the accuracy and value of consumer demographic information have been emphasized. Additionally, in the classification and prediction section, a kind of "customization" has been performed with an emphasis on market segmentation. This research used GMM and MLP machine learning algorithms as a creative way to cluster and classify consumers. [ABSTRACT FROM AUTHOR]

Improving engineering design in the context of market systems requires a deep understanding of the decision-making processes of multiple interacting stakeholders and how they affect the success of new products. One key group of stakeholders in this system is consumers, who make purchase choices that directly influence each product's market share and profits. Since real-world individual decisions are influenced by social communications, supporting product development efforts with social network analysis can enable producers to predict demand much more accurately. This article presents an agent-based modeling (ABM) framework for design for market systems analysis that incorporates social network word-of-mouth (WOM) recommendations. To investigate influences of homophily-driven WOM and network structures on consumer preferences and the prediction of market demand, the random and small-world networks are generated based on the concept of homophily to study the differences in the emergent system-level behaviors. We compare the output of the models against a similar model that excludes WOM influences, using a case study of the top-selling midsize sedans in the US automobile industry. The results show that the addition of WOM improves the ability to accurately forecast consumer demand in a statistically significant way. This suggests that producers who invest in supporting their product development efforts with design for market systems analyses that account for social networks may be able to better optimize their decision-making and increase their market success. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal how social network marketing (SNM) can affect consumers' purchase behavior (CPB). We used the combination of structural equation modeling (SEM) and unsupervised machine learning approaches as an innovative method. The statistical population of the study concluded users who live in Hungary and use Facebook Marketplace. This research uses the convenience sampling approach to overcome bias. Out of 475 surveys distributed, a total of 466 respondents successfully filled out the entire survey with a response rate of 98.1%. The results showed that all dimensions of social network marketing, such as entertainment, customization, interaction, WoM and trend, had positively and significantly influenced consumer purchase behavior (CPB) in Facebook Marketplace. Furthermore, we used hierarchical clustering and K-means unsupervised algorithms to cluster consumers. The results show that respondents of this research can be clustered in nine different groups based on behavior regarding demographic attributes. It means that distinctive strategies can be used for different clusters. Meanwhile, marketing managers can provide different options, products and services for each group. This study is of high importance in that it has adopted and used plspm and Matrixpls packages in R to show the model predictive power. Meanwhile, we used unsupervised machine learning algorithms to cluster consumer behaviors. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a profound psychological and behavioral impact on people around the world. Consumer purchase behaviors have thus changed greatly, and consumer services companies need to adjust their business models to adapt to this change. From the perspective of consumer psychology, this paper explores the impact of consumer purchase behavior changes over the course of the pandemic on the business model design of consumer services companies using a representative survey of 1,742 individuals. Our results show that changes in consumer purchase behavior have a significant impact on the design of consumer services firms' business models. Specifically, changes in consumers' purchase object, motive, and timeframe are more likely to spark a novelty-centered business model design, whereas changes in purchase method tend to inspire an efficiency-centered one. Our findings provide a theoretical reference for consumer services companies in designing business models when faced with unexpected crises. [ABSTRACT FROM AUTHOR]

Little is known about consumers' behavior especially when purchasing and consuming utilitarian products in developing countries. Hence, the aim of the present work is to introduce a modern and native model of consumer behavior in the selection of utilitarian products with a focus on discount chain stores. The model helps to understand and select practical marketing strategy. The data were gathered from semi-structured interviews and a review of the literature in the qualitative section of the research. A grounded theory including open coding, axial coding and selective coding was used to analyze the data. In the quantitative section of the research, the data were gathered through a questionnaire. Modeling of structural equations was also done to analyze the model. For the proposed model of consumer purchasing behavior, we found 22 factors in seven main categories including utilitarian motivations, hedonic motivations, store attributes, individual factors, functional marketing strategies, promotion and customer loyalty. The quantitative results showed that buying motivations, store attributes and marketing strategies have positive impacts on purchase intention, but gender and age have no positive impact in this regard.

The COVID-19 pandemic has had a profound psychological and behavioral impact on people around the world. Consumer purchase behaviors have thus changed greatly, and consumer services companies need to adjust their business models to adapt to this change. From the perspective of consumer psychology, this paper explores the impact of consumer purchase behavior changes over the course of the pandemic on the business model design of consumer services companies using a representative survey of 1,742 individuals. Our results show that changes in consumer purchase behavior have a significant impact on the design of consumer services firms’ business models. Specifically, changes in consumers’ purchase object, motive, and timeframe are more likely to spark a novelty-centered business model design, whereas changes in purchase method tend to inspire an efficiency-centered one. Our findings provide a theoretical reference for consumer services companies in designing business models when faced with unexpected crises.

The declared state of emergency and the measures taken against the spread of coronavirus by governments have increased Internet shopping. All companies, regardless of size and type of business activity, had to adapt their business models to the new circumstances through transformation of their business processes and offering products or services tailored to the changing customer behavior. This study aims to analyze the peculiarities of online sales during the COVID-19 health crisis via the integration of classic and modern data analysis methods. The purpose of the paper is to identify the main factors determining user behavior and examine their impact on customer satisfaction in e-commerce. The survey method and structural equation modeling (SEM) were used to recognize the dependencies between variables from the online users’ perspective. The satisfaction determinants indicated and described in the paper affect differently the perceived value for the customers. As this value is subjective and dynamic, this study developed a reliable system for e-commerce factor evaluation. Using the proposed methodology, companies can constantly monitor and assess indicators influencing customer satisfaction and gain awareness of consumer behavior’s dynamics in online shopping. e-commerce marketers can employ the obtained results to decide how to organize order execution and optimize supply chains. Identifying the most important components of the e-commerce value, managers of online retailers can better run online sales platforms, increase customer loyalty, and thus, improve company’s online performance.

Copyright of Ad-minister is the property of Universidad EAFIT and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There is a limited understanding of consumer behavior, especially consumer choice behavior when shopping for and consuming enjoyable products from chain stores, and there is always a discount in developing countries. The purpose of the present study is to design a conceptual model of consumer shopping behavior in selecting enjoyable products based on factors affecting purchase. The research approach is mixed and applied in terms of purpose. Thus, in the qualitative section, the data were collected through semi-structured interviews and used the data theory strategy of open, axial and selective coding as well as the basic model of this theory to achieve the research model. The sampling method used is snowball sampling which is one of the targeted sampling methods. Also in the quantitative section, the data were collected through a questionnaire and a descriptive survey method using structural equation modeling to analyze and explain the proposed model. The qualitative results of the research in the form of a validated and fitted model include six dimensions of pleasant shopping motivations, store characteristics, individual characteristics, strategies, communication and customer loyalty, and three dimensions. The quantitative results of the study show that pleasant shopping motivations, store characteristics, individual characteristics have a significant and positive impact on strategy and communication. Strategies and communications also have a positive impact on customer loyalty in choosing enjoyable products.

The purpose of this paper is to reveal how social network marketing (SNM) can affect consumers’ purchase behavior (CPB). We used the combination of structural equation modeling (SEM) and unsupervised machine learning approaches as an innovative method. The statistical population of the study concluded users who live in Hungary and use Facebook Marketplace. This research uses the convenience sampling approach to overcome bias. Out of 475 surveys distributed, a total of 466 respondents successfully filled out the entire survey with a response rate of 98.1%. The results showed that all dimensions of social network marketing, such as entertainment, customization, interaction, WoM and trend, had positively and significantly influenced consumer purchase behavior (CPB) in Facebook Marketplace. Furthermore, we used hierarchical clustering and K-means unsupervised algorithms to cluster consumers. The results show that respondents of this research can be clustered in nine different groups based on behavior regarding demographic attributes. It means that distinctive strategies can be used for different clusters. Meanwhile, marketing managers can provide different options, products and services for each group. This study is of high importance in that it has adopted and used plspm and Matrixpls packages in R to show the model predictive power. Meanwhile, we used unsupervised machine learning algorithms to cluster consumer behaviors.

Packaging in marketing literature is considered as a part of Product or brand. Packaging is one the most important factors in the field of production and marketing. Unfortunately, in our countray, the majority of packaging activities are traditional and research plays a minor role. It seems that practiotioners have a little knowedge apout packaging and its importance in marketing. The aim of present study is to investigate the relationship between packaging information and consumer purchase behavior. By using convenient sampling, 384 questionares were distributed and used for statistical analysis. The validity and reliability of questionaires were validated. Finidngs showed that there was a meaningful correlation between packaging information (legal, marketing and nutrition information) and consumer purchase behaviors. Production and expiration date, price and ISO information were the most imporatant legal information. Brand and packaging materials were the most imporatant marketing information. According to regression analysis, packaging information explains 65.6 percent of change in the dependent variable (consumer purchase behavior).

In order to study the elements of Zara’s “civilian fashion” brand image and the relationship between brand image and consumer’s purchase behavior, based on the theory of brand image evaluation, combined with the theory of perceived value and consumer’s behavior, Zara’s “civilian fashion” brand image was proposed, which was composed of four dimensions and twenty-one indicators. Based on this, the corresponding theoretical model was constructed, four hypotheses about the relationship between brand image and consumer purchase behavior were put forward and empirical tested. The results show that subjective value, communication value and product image all have positive effects on consumers’ purchase behavior. It is believed that fashion brand should build and spread the brand image of “civilian fashion” from close to customers, spreading culture and creating products, so as to improve the brand identification and competitiveness. [ABSTRACT FROM AUTHOR]

Recent changes of the environment and in the society have altered consumers’ preferences and brought new concerns among local communities regarding environmental protection and organizations responsibility, the adoption of environmentally friendly strategies, as well as offering more sustainable products. Consumers tend to select retailers based on their focus on environmental friendly products and on various “green” strategies regarding waste disposal, package recycling, etc. This study aims to highlight Romanian and Slovak consumers’ attitudes towards purchasing of goods from retailers that strive a clear focus on environmental responsibility and environmental friendly practices in apparel, footwear and sportswear retail. By means of a quantitative research based on a questionnaire administered to consumers of international retail chains with operations in both countries, the authors highlight differences in their perceptions and attitudes for buying green apparel, footwear and sportswear. Whereas Millennials and Gen Xers consumers in Romania and Slovakia believe that international apparel, footwear and sportswear retailers are less concerned about environmentally responsible behavior and the need of selling green products, Baby Boomers are more sensitive to such aspects and carefully select retailers according to their green strategy. This research provides specific findings about attitudes of different consumers’ generations within two emerging European countries (Romania, Slovakia).

This study aims to examine the differences between several empirical articles on the theory of planned behavior. Theory of planned behavior provides a framework for studying attitudes toward behaviors that postulate three determinants of conceptual intent. Specifically, the intention is based on the variables of attitude toward behavior, subjective norms, and perceived behavioral control. Although this theory has been used frequently, there are still differences in outcomes in explaining attitudes toward behavior. The results show that there is still a different view of the theory of planned behavior so it is necessary to identify the gaps that occur in this theory. For further research is expected to expand and enrich the discussion of the theory of planned behavior

Copyright of Wool Textile Journal is the property of National Wool Textile Science & Technology Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The market participation and development of major manufacturers of next-generation green vehicles is accelerating in recent years. The results of this study are as follows: Consumer type (personal value pursuit type, price value pursuit type) was significant difference between consumer. The results of this study were as follows: First, there was no significant difference in the characteristics of consumers (gender, age, monthly average income) and purchase intention according to age, gender and monthly average income, Image has a positive (+) impact on eco-friendly vehicles. This suggests that the development and market participation of next - generation green vehicles is accelerating and consumers 'interest is increasing, and the characteristics of environment - friendly vehicles and the government' s policy support are important factors. [ABSTRACT FROM AUTHOR]

Copyright of Electronic Turkish Studies is the property of Electronic Turkish Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recommender systems appear all across the internet. For e-retailers, this represents an opportunity to get more and niche products before customers' eyes. However, we find that while implementing recommender systems does increase overall sales figures, it does not generally improve the relative sales for niche items, leading to a rich-get-richer situation. We find, across a wide range of product categories, that the use of traditional collaborative filters (CFs) is associated with a decrease in sales diversity relative to a world without product recommendations. The decrease in aggregate sales diversity may not always be accompanied by a corresponding decrease in individual-level consumption diversity. In fact, it is even possible for individual consumption diversity to increase as aggregate sales diversity decreases. CFs help individuals explore new products, but similar users still end up exploring the same kinds of products, resulting in concentration bias at the aggregate level. There is one insight for management: Traditional collaborative filters carry the unintended consequence of increasing concentration bias. A firm interested in exposing consumers to a broader assortment of products may prefer a different design from another simply interested in maximizing sales. We investigate the impact of collaborative filtering recommender algorithms (e.g., Amazon's "Customers who bought this item also bought") commonly used in e-commerce on sales diversity. We use data from a randomized field experiment run on the website of a top retailer in North America across 82,290 products and 1,138,238 users. We report four main findings. First, we demonstrate and quantify across a wide range of product categories that the use of traditional collaborative filters (CFs) is associated with a decrease in sales diversity relative to a world without product recommendations. Furthermore, the design of the CF matters. CFs based on purchase data are associated with a greater effect size than those based on product views. Second, the decrease in aggregate sales diversity may not always be accompanied by a corresponding decrease in individual-level consumption diversity. In fact, it is even possible for individual consumption diversity to increase while aggregate sales diversity decreases. Third, copurchase network analyses show that while recommenders can help individuals explore new products, similar users still end up exploring the same kinds of products, resulting in concentration bias at the aggregate level. Fourth and finally, there is a difference between absolute and relative impact on niche items. Specifically, absolute sales and views for niche items in fact increase, but their gains are smaller compared with the gains in views and sales for popular items. Thus, whereas niche items gain in absolute terms, they lose out in terms of market share. We discuss economic impacts and managerial implications. The online appendices are available at https://doi.org/10.1287/isre.2018.0800. [ABSTRACT FROM AUTHOR]

The present study aims at determining and ranking the most influential elements for workers to choose a continuing education university program. In order to carry out this quantitative study, we applied a questionnaire to 805 students in the special programs of five Chilean universities in different cities. Through factorial analysis of the main components, we identified eleven dimensions which describe the aspects individuals consider in their decisions. Out of the eleven aspects, six are the most relevant in the process: the communication effort, the sense of self-fulfillment, the characteristics of the program, the reference groups, the institutional image and the influence of the family. The results comprise a valuable asset for the design and execution process of efficient and effective marketing strategies adopted by higher education institutions. [ABSTRACT FROM AUTHOR]

In recent years, the importance of corporate social responsibility activities, especially for multinational companies, has been evidently understood and these activities are started to be used more often. The timing and communication strategies regarding these activities, on the other hand, have gained weight in the literature and been widely analyzed. According to the findings of those studies, consumers might give different responses to proactive and reactive corporate social responsibility activities. Nevertheless, there is no consensus in the literature among these findings. Moreover, it is also found that different cultural settings yield different results in terms of the effects of corporate social responsibility activities on consumer purchase behaviors. In our study, together with the effects of corporate social responsibility activities on consumer purchase behavior, the effect cultural differences on this relationship have also been analyzed. In the study, the difference between Dutch and Turkish consumers is analyzed by using a vignette study. At the end of the study, the effect of timing of corporate social responsibility activities on consumer purchase behavior is statistically proven. Moreover, some differences between abovementioned cultures with regard to the relationship between corporate social responsibility activity timing and consumer purchase behavior, is also found to be statistically significant. The implications of those findings for the literature as well as managerial perspectives are discussed at the end of the study. [ABSTRACT FROM AUTHOR]

Customers’ behavior during purchase from internet likewise traditional purchase behavior model derives from a series of cultural, social, personal and/or psychological factors. To increase knowledge and information of managers, marketers and researchers at e-marketing, this research had intended to examine effect of motivation as one of effective internal factors in consumer behavior and purchase behavior in internet. The theoretical framework of research was created based on the studies conducted at this area which individuals’ purchase motives were examined in two functional and non-functional motives and internet purchase behavior was examined in three dimensions of purchase intention, purchase acceptance and purchase continuity, which eight hypotheses were designed in line with the proposed model. The statistical population consists of the internet purchasers of NetBarg Company across Iran. Questionnaire was used as the instrument to collect data, which 166 customers of internet NetBarg shopping center were selected as the sample group. After collecting data, the hypotheses were analyzed via correlation test, regression analysis and path analysis technique. Results from investigations indicated that functional motives have a direct relationship with intention, acceptance and continuity of internet purchase and non-functional motives have a direct relationship with acceptance and intention of internet purchase.

Business process is under the IT revolution which is transforming the way we do the business. Basic business operations like decision making, customer service, marketing strategies, human resource management are being reformed with the use of IT. It also plays a vital role in the lives of people. Every field of human activity, may it be his daily life, official life, everything is now influenced under the cover of IT. It is used for storing, protecting, processing, securing, transmitting, receiving, and retrieving information. Keeping in mind the various benefits of IT, in the present paper an attempt has been made to study the impact of IT on consumer purchase behavior for non life insurance products in Delhi/ NCR. The findings highlight that IT has a great influence on consumer purchase behavior. It is argued that the outcome of the study will certainly be helpful for the marketers to define their marketing strategies accordingly. [ABSTRACT FROM AUTHOR]