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Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids
Abstract
Despite the explosive growth of electronic commerce and the rapidly increasing number of consumers who use interactive media (such as the World Wide Web) for prepurchase information search and online shopping, very little is known about how consumers make purchase decisions in such settings. A unique characteristic of online shopping environments is that they allow vendors to create retail interfaces with highly interactive features. One desirable form of interactivity from a consumer perspective is the implementation of sophisticated tools to assist shoppers in their purchase decisions by customizing the electronic shopping environment to their individual preferences. The availability of such tools, which we refer to as interactive decision aids for consumers, may lead to a transformation of the way in which shoppers search for product information and make purchase decisions. The primary objective of this paper is to investigate the nature of the effects that interactive decision aids may have on consumer decision making in online shopping environments.
While making purchase decisions, consumers are often unable to evaluate all available alternatives in great depth and, thus, tend to use two-stage processes to reach their decisions. At the first stage, consumers typically screen a large set of available products and identify a subset of the most promising alternatives. Subsequently, they evaluate the latter in more depth, perform relative comparisons across products on important attributes, and make a purchase decision. Given the different tasks to be performed in such a two-stage process, interactive tools that provide support to consumers in the following respects are particularly valuable: (1) the initial screening of available products to determine which ones are worth considering further, and (2) the in-depth comparison of selected products before making the actual purchase decision. This paper examines the effects of two decision aids, each designed to assist consumers in performing one of the above tasks, on purchase decision making in an online store.
The first interactive tool, a recommendation agent (RA), allows consumers to more efficiently screen the (potentially very large) set of alternatives available in an online shopping environment. Based on self-explicated information about a consumer's own utility function (attribute importance weights and minimum acceptable attribute levels), the RA generates a personalized list of recommended alternatives. The second decision aid, a comparison matrix (CM), is designed to help consumers make in-depth comparisons among selected alternatives. The CM allows consumers to organize attribute information about multiple products in an alternatives × attributes matrix and to have alternatives sorted by any attribute.
Based on theoretical and empirical work in marketing, judgment and decision making, psychology, and decision support systems, we develop a set of hypotheses pertaining to the effects of these two decision aids on various aspects of consumer decision making. In particular, we focus on how use of the RA and CM affects consumers' search for product information, the size and quality of their consideration sets, and the quality of their purchase decisions in an online shopping environment.
A controlled experiment using a simulated online store was conducted to test the hypotheses. The results indicate that both interactive decision aids have a substantial impact on consumer decision making. As predicted, use of the RA reduces consumers' search effort for product information, decreases the size but increases the quality of their consideration sets, and improves the quality of their purchase decisions. Use of the CM also leads to a decrease in the size but an increase in the quality of consumers' consideration sets, and has a favorable effect on some indicators of decision quality.
In sum, our findings suggest that interactive tools designed to assist consumers in the initial screening of available alternatives and to facilitate in-depth comparisons among selected alternatives in an online shopping environment may have strong favorable effects on both the quality and the efficiency of purchase decisions—shoppers can make much better decisions while expending substantially less effort. This suggests that interactive decision aids have the potential to drastically transform the way in which consumers search for product information and make purchase decisions.
... For BLV users, navigating unfamiliar websites can be particularly challenging due to the need to understand and interact with unique website elements and layouts, which can be confusing and time-consuming. This problem is especially evident on shopping websites, where visually appealing but complex designs often take precedence over accessibility [23]. Shopping websites frequently use intricate layouts, dynamic content, and numerous filters or categories that may not be accessible to screen readers, further complicating the navigation experience for BLV users. ...
... Moreover, since website designs vary significantly, unfamiliar websites can impose an additional burden on visually impaired users and it is recommended that websites use simple structures to be more accessible [29]. Interfaces with advanced interactive features, such as complex layouts or designs, particularly in shopping websites [23], exacerbate this issue. Stangl et al. revealed that while information on shopping websites is often presented through images, the accompanying image descriptions are frequently inadequate, leading visually impaired users to seek more detailed information. ...
Online interactions and e-commerce are commonplace among BLV users. Despite the implementation of web accessibility standards, many e-commerce platforms continue to present challenges to screen reader users, particularly in areas like webpage navigation and information retrieval. We investigate the difficulties encountered by screen reader users during online shopping experiences. We conducted a formative study with BLV users and designed a web browser plugin that uses GenAI to restructure webpage content in real time. Our approach improved the header hierarchy and provided correct labeling for essential information. We evaluated the effectiveness of this solution using an automated accessibility tool and through user interviews. Our results show that the revised webpages generated by our system offer significant improvements over the original webpages regarding screen reader navigation experience. Based on our findings, we discuss its potential usage as both a user and developer tool that can significantly enhance screen reader accessibility of webpages.
... L. Manning and J.H. Grant Trends in Food Science & Technology 156 (2025) 104811 (Monghasemi et al., 2015); benefit versus harm (O'Connor et al., 2003); speed of response versus accuracy (Franks et al., 2003;Häubl & Trifts, 2000), effort required versus accuracy (Häubl & Trifts, 2000); and effectiveness of intervention versus safety (Kim & Lee, 2022). Some values are more resistant to trade-offs than others. ...
... L. Manning and J.H. Grant Trends in Food Science & Technology 156 (2025) 104811 (Monghasemi et al., 2015); benefit versus harm (O'Connor et al., 2003); speed of response versus accuracy (Franks et al., 2003;Häubl & Trifts, 2000), effort required versus accuracy (Häubl & Trifts, 2000); and effectiveness of intervention versus safety (Kim & Lee, 2022). Some values are more resistant to trade-offs than others. ...
... When making purchasing decisions, consumers frequently lack the opportunity to thoroughly evaluate all available options concerning the products or services they intend to purchase (Häubl & Trifts, 2000). In such cases, consumers pick up information from diverse channels, such as websites, consumer ratings, product reviews, and suggestions from acquaintances and family members (Chen et al., 2004). ...
... Another reason is that the recommendations of consumers with similar product preferences reduce the search costs of finding suitable products (Pathak et al., 2010). In this way, consumers can make confident decisions in their purchasing process by reducing the number of products to be examined among alternatives and the time required for decision-making (Metzger et al., 2010;Hostler et al., 2005;Häubl & Trifts, 2000). The fact that individuals' resort to heuristics instead of evaluating all alternatives in decisionmaking processes makes consumers more prone to herd behaviour (Ali et al., 2021). ...
The objective of this paper is to explore the effects of herding and anchoring effects, two behavioural economics concepts, on perceived source credibility, which is commonly utilized in marketing research. These cognitive shortcuts that shape consumers' decisions reduce their perceived risk or help them make decisions under uncertainty. The literature contains a limited amount of research on the topic that addresses source credibility in terms of behavioural economics. Within this framework, the study is anticipated to enhance the body of literature through its chosen topic and methodology. When reviewing research undertaken within the marketing domain, the experimental design method has been used in very few studies. In this context, in the experimental designs created within the scope of the study, various scenarios were designed on the basis of follower number (high/low) to evaluate the impact of herd behaviour on the credibility of the source and on the substance of news about the influencer (positive/negative) to measure the anchoring effect. After the participants were shown one of the scenarios, they were given questionnaires with statements about source credibility to answer, and how the perception of source credibility differs according to herd behaviour and the anchoring effect was investigated. Instagram influencers were used in the experimental designs created in the study because Instagram application is increasingly preferred over other social media platforms, is more effective in terms of marketing communication, is increasingly included in the marketing strategies of businesses and is preferred by the young population. Within the framework of this research, data were gathered via an online survey administered to a total of 727 students enrolled in various departments across universities in Turkey. These data were subjected to one-way ANOVA via the SPSS program. Research findings indicate that herding behaviour significantly affects the perceptions of the source credibility, expertise, and attractiveness of social media influencers. Furthermore, anchoring significantly affects the source credibility perceptions and expertise, trustworthiness, and attractiveness subdimensions. However, in scenarios where the number of followers and anchors are identical, a statistically significant difference was not found in the perception of source credibility in relation to the gender of the influencer.
... Pelanggan menjalani proses penilaian subjektif ketika membuat keputusan pembelian, dianggap sebagai resolusi setelah melalui serangkaian kegiatan dan penelitian (Hee et al., 2022). Tahap akhir melibatkan evaluasi mendalam terhadap atribut produk yang dianggap penting, yang kemudian membawa pada keputusan pembelian (Haubl & Trifts, 2000). Dalam mengambil keputusan pembelian, konsumen jarang memiliki informasi lengkap untuk menilai kualitas produk (Aisyah & Hamzah, 2022). ...
This study aims to investigate the effect of price, brand image, lifestyle, andproduct quality on purchasing decisions for Cargloss helmets. The research method uses a quantitative approach with a questionnaire survey of 100 consumer respondents who buy Cargloss helmets. The results show that price, brand image, lifestyle, and product quality have a positive and significant effect on purchasing decisions. Overall, these factors simultaneously also have a positive and significant influence. Companies are advised to set competitive prices with market research to maintain the attractiveness of Cargloss. To build brand identity, companies can emphasise the speciality of Cargloss helmets in design, innovation and other added values. Promotion is also needed to associate Cargloss helmets with consumers' lifestyles. The company management should invest in quality control, quality raw materials, and adoption of latest technology in the production process.
... Recognizing the gravity of this issue in the context of coffee selection, this study endeavors to introduce an innovative approach to alleviate choice overload and enhance the user experience. One of the ways to mitigate the choice overload issue is by using recommender systems (Haubl & Trifts, 2000). According to Roy and Dutta (2022), a recommender system is a system that, from an extended selection of alternatives, can either guide the user in a personalized manner to useful objects or it can deliver tailored recommendations as output. ...
Coffee, a typical beverage consumed worldwide, offers various options, from bean origin to brewing methods. However, this abundance of choice often leads consumers to experience decision-making challenges, a phenomenon known as choice overload. Therefore, this study focuses on developing and implementing a recommendation application to help users make informed coffee choices based on their preferences. The study employs a system development life cycle (SDLC) approach and utilizes content-based filtering techniques to achieve the purpose. Data for this study was gathered from three prominent coffee shops: Zus Coffee Shop, Richiamo Coffee Shop and Gigi Coffee Shop, providing a diverse dataset for analysis. The study employs usability testing to evaluate the usefulness, perspicuity, dependability, and attractiveness of the developed recommendation application. Through rigorous testing, we assess user acceptance and overall system performance. The results indicate a significant reduction in choice overload and an enhanced user experience, validating the competence of the recommendation application. The study implies that by using a content-based filtering recommendation system, coffee drinkers can enjoy more personalized suggestions tailored to their taste preferences, such as roast level, milk type, etc. For users who may feel overwhelmed by the variety of options at a coffee shop, this system simplifies the decision process by recommending coffee types that match their stated preferences. By exploring avenues such as collaborative filtering, sentiment analysis, and incorporating additional user feedback, we aim to further enhance the accuracy and personalization of coffee recommendations, ultimately improving the overall coffee selection experience for consumers.
... In general, the decision-making process consists of five stages: (1) problem recognition; (2) search for alternative information; (3) alternative evaluation and selection; (4) choice and purchase; (5) the post-purchase process (Moutinho, 1987). Building on this foundation, Haubl and Trifts (2000) proposed a two-stage decision-making theory focused on studying consumer behavior when buying goods or services. The first stage is the search for information about the product, and the second is the comparison and evaluation of alternatives. ...
The constant change in consumer preferences requires adjusting sales strategies according to the consumer’s current needs. The study aims to cluster the consumers of tourism products based on the factors influencing their decision-making process when choosing tourism products and to classify them according to the marketing mix. The study is based on the analysis of data from 196 respondents in the Lviv region, collected through an online survey using Google Forms in the first decade of 2023. The sample is representative, as it was calculated considering the population of the Lviv region aged 16 and above, ensuring the results’ reliability and relevance. The results revealed that representatives of each cluster are, on average, willing to spend up to 10,000 UAH per person during their vacation. In the decision-making process regarding the purchase of components of a tourist product, accommodation holds the most significant importance for representatives of the first and second clusters (4.51 and 3.27, respectively), insurance is the most important for the third cluster (4.71), and food is the priority for the fourth cluster (2.54). The decisive components of tourist services and risks for all clusters include up-to-date information about the vacation destination and pandemics/diseases, although the significance of their influence varies. Additionally, the clusters differ regarding the elements of place and promotion of tourist products. The results demonstrate that the marketing mix elements vary across clusters despite certain similarities in respondents’ assessments.
... Traditionally, buying decisions involved a time-consuming and effortintensive process, as customers were required to physically visit stores, assess product availability, engage with items firsthand, and occasionally compare them to similar offerings in competing stores. This often led to more rational decisions by customers (Häubl and Trifts [32], as cited in Chung et al. [16]). Nowadays, the landscape has changed significantly with the emergence of e-commerce and digital payment. ...
This study examines the impact of Buy-Now-Pay-Later (BNPL) services on the buying and financial behaviors of Saudi students at Majmaah University. The research focuses on understanding how BNPL usage influences impulse buying, purchase intention, savings, and investment decision-making. Despite the increasing adoption of BNPL services globally, research specifically targeting the Saudi university student population remains limited. This study addresses this gap by exploring the factors that drive BNPL adoption among this digitally-savvy generation, which in Saudi is also experiencing new economic conditions under the Vision 2030 initiative. Using a convenience sampling method, a closed-ended Arabic-language survey was distributed via social media platforms and email to a sample of Majmaah University students; 218 responses were obtained. The survey comprised six demographic questions and 18 items to be rated on a 5-point Likert scale to measure respondents’ attitudes and financial behaviors. The results indicate that while BNPL services have minimal impact on impulse buying, BNPL usage negatively affects students’ financial behaviors, particularly, in terms of personal savings and investments. Nonetheless, respondents expressed strong willingness to continue using such services. These insights contribute to a deeper understanding of BNPL’s role in shaping financial and purchasing behaviors among university students, highlighting the need for further research and policy considerations in this context.
... Pada fase pertama, konsumen biasanya menyaring sejumlah besar produk yang tersedia dan mengidentifikasi sejumlah alternatif yang paling menjanjikan (Song et al., 2021;Fernandes et al., 2021). Sistem pendukung keputusan dapat mengurangi beban kerja pencarian informasi produk, mengurangi rentang pertimbangan, dan meningkatkan kualitas keputusan, yang menghasilkan proses dalam memutuskan pembelian dapat melalui beberapa tahapan sebelum benarbenar memutuskan pembelian produk pembelian (Song et al., 2021;Haubl & Trifts, 2014;Santosarteaga et al., 2020). ...
This research aims to identify variations or combinations of attributes that form customer preference for hijab in Jombang district. The method used is a descriptive-exploratory method. Data analysis uses conjoint analysis. The attribute factors that form customer preferences analyzed in this research are materials, colors, models and motifs. Sampling used accidental sampling technique, with a total of 100 respondents. The results show that the product combinations in hijab products of Rumah Anita that are consumer preferences are ceruty chiffon hijab material, soft hijab colors, pashmina hijab models and plain hijab motifs. In choosing Rumah Anita’s hijab products, the order of the most important attributes that influence consumer purchasing decisions is that the first is that consumers prioritize the model attribute, the second is the motif attribute, the third is the material attribute and the last is the color attribute.
... These include but are not limited to traditional window displays (Sen et al., 2002), virtual presentations (González et al., 2021), recommendation signage (bestsellers or editor's picks) (Goodman et al., 2013), platform endorsements (Amazon's Choice) (Bairathi et al., 2024), and quantified claims (Yu and Urminsky, 2023). The evidence for these simple modifications altering choice behavior is conclusive and indisputable across a wide spectrum of economic activities (e.g., for the labor market, Horton, 2017; for hospitality and tourism, Litvin et al., 2008; for music streaming services, Adomavicius et al., 2018;Li et al., 2007; for e-commerce of commodities or goods, Goodman et al., 2013;Häubl and Trifts, 2000;Rowley, 2000;Senecal and Nantel, 2004;Vijayasarathy and Jones, 2000). ...
We explore the influence of framing on decision-making, where some products are framed (e.g., displayed, recommended, endorsed, or labeled). We introduce a novel choice function that captures observed variations in framed alternatives. Building on this, we conduct a comprehensive revealed preference analysis, employing the concept of frame-dependent utility using both deterministic and probabilistic data. We demonstrate that simple and intuitive behavioral principles characterize our frame-dependent random utility model (FRUM), which offers testable conditions even with limited data. Finally, we introduce a parametric model to increase the tractability of FRUM. We also discuss how to recover the choice types in our framework.
... According to Kotler and Keller (2016), information accessibility can increase consumer confidence, which has a positive impact on purchasing decisions. Increased accessibility of information through digital platforms can speed up the consumer decisionmaking process and lower the level of uncertainty in purchases (Häubl & Trifts, 2000). Thus, good information accessibility not only makes it easier for consumers to gain a deeper understanding of mortgage products, but also plays an important role in influencing their confidence in making the right purchase decision. ...
Buying a simple house is often influenced by various factors, including the accessibility of information and the ease of applying for a Home Ownership Loan (KPR). This study aims to analyze the influence of Information Accessibility and Ease of Mortgage Application through marketing strategies on Simple House Purchase Decisions in Balikpapan City. The study used a quantitative method with a survey approach to 200 selected respondents using the purposive sampling technique. The data was analyzed using Structural Equation Modeling (SEM) assisted by Smart-PLS software. The results showed that Information Accessibility had a significant influence on Simple Home Purchase Decisions (path coefficient 0.630; T-statistic 6,023; p-value 0.000) and for the Ease of Mortgage Application (line coefficient 0.805; T-statistic 22,845; p-value 0.000). The ease of applying for a mortgage also has a significant effect on the Decision to Purchase a Simple House (line coefficient 0.234; T-statistic 1,928; p-value 0.049). An R-square value of 0.618 shows that the research model is able to explain 61.8% of the variability of purchase decisions. These findings underscore the importance of a digital-based marketing strategy that focuses on information transparency and simplifying administrative processes to improve consumer purchasing decisions.
... While making purchase decisions, consumers often cannot evaluate all available alternatives in great depth and, thus, tend to use two-stage processes to reach their decisions. At the first stage, consumers typically screen many available products and identify a subset of the most promising alternatives (Häubl and Trifts 2000). This means a sequential choice problem is there. ...
The article considers the assortment planning problem with respect to trustworthy reviewers. The trustworthiness of the product review and rating is based on whether the reviewer is rational or irrational. The average review ratings and comments are affected by the average trustworthiness. On the other hand, consumers have attention spans, i.e., the maximum number of products they are willing to view and inspect sequentially before purchasing a product or leaving the platform empty-handed when the attention span gets exhausted. The current paper provides an assortment planning model that maximizes revenue while considering trustworthy online product reviews as the quality by considering a threshold number of reviews and prices. This, in turn, is expected to minimize the information asymmetry within the decision-making process and identify the paid reviewers or manipulative reviews.
... Personalized recommendations aid customers in making informed product choices, as the suggestions are tailored to match their needs and interests. Consequently, customers can make higher-quality decisions (Diehl et al., 2003;Häubl & Trifts, 2000;Tsekouras et al., 2020;Xiao & Benbasat, 2007), ultimately leading to heightened levels of customer satisfaction and loyalty (Liang et al., 2006;Tsekouras et al., 2020). These favorable customer responses contribute significantly to the overall success of firms. ...
This research explores the transformative impact of the Internet of Things (IoT) on customer experiences within the retail sector. Focusing on personalized recommendations, location-based services, and interactive displays, the study reveals key findings that underscore the potential of IoT technologies to enhance customer engagement and satisfaction. Through the integration of real-time data analytics and machine learning algorithms, personalized recommendations proved instrumental in influencing customer behavior, driving increased satisfaction and loyalty. Location-based services, leveraging geospatial data, not only facilitated personalized navigation and targeted promotions but also demonstrated a positive correlation with enhanced customer loyalty. Additionally, the integration of interactive displays, empowered by IoT, significantly contributed to heightened customer engagement and overall satisfaction. The research suggests implications for the retail industry, advocating for the strategic adoption of IoT to optimize customer experiences. Ethical considerations and privacy concerns emerged as crucial areas for future exploration, alongside the potential for comparative studies and longitudinal analyses across diverse retail sectors.
... Algorithms can shape and mediate relationships on a variety of online platforms, such as social media and messaging apps [6,43,55,114], online marketplaces [8,61], and dating platforms [26]. While such algorithms offer opportunities to maintain old relationships and build new ones, they can also introduce harm to people's social relationships [43,55,57]. ...
On online platforms, algorithms help us build and manage our relationships. However, their invisible interventions might also pose harm to these connections. Dating platforms offer a prime example where, despite extensive research on human-inflicted harm, the potential harm from the algorithms themselves, and user strategies for mitigating them, remains largely unexplored. In our analysis of 7,043 reviews and interviews with 30 Tinder users, we unveiled how users perceive algorithmic harm as damaging self-esteem, sabotaging potential relationships, encouraging antisocial behavior, and misrepresenting or marginalizing certain identities. We introduce a new algorithmic folk theory, the "conflict of interest" theory, perceived to perpetuate these harms. This theory encapsulates users' sense of a contradiction between the dating platform's promise of finding the perfect partner (leading to discontinued use of Tinder) and its commercial interest in retaining users to increase revenue. Users suspected various algorithmic processes pursuant to this theory, such as (a) throttling profile visibility, (b) manipulating users' matches, and (c) recommending large quantities of profiles that will not lead to matches. They also described various strategies in resistance or defense of these suspected algorithmic processes, such as engaging in counter-intuitive behaviour to disrupt the unfavorable algorithmic processes or leveraging location based filtering for match variety and safety. We conclude by discussing how the perceived algorithmic harms can inform the development of new algorithmic implementations that balance both user and company interests.
... First, Jellycat engages with consumers through social media platforms (such as Facebook, Instagram, etc.), publishing product images, videos, and stories to increase brand awareness and appeal. Whether shopping online or in person, interactive shopping experiences create more engagement, these types of experiences are often memorable, can increase customer satisfaction, encourage customers to engage with the brand, and can lead to more customers talking to others about their experiences, whether on social media or in person with friends and family [10]. The combination of performance and interactive shopping not only makes the product more childlike and unique but also satisfies consumers with a beautiful shopping experience. ...
This paper is based on Jellycat's new marketing strategy of selling toys with a additional show, and there is only little research on the influence of such a marketing strategy on Jellycat's brand by scholars. Therefore, this paper aims to study the influence of Jellycat's offline stores by combining performance and sales. This paper uses qualitative data collection on the website and different models to analyze Jellycat's marketing strategy, including marketing mix, SWOT analysis, and Pestle analysis. The research results show that the new sales method, that is, on-site sales with corresponding short performances, can affect multiple factors on many levels. For example, the price of the product will increase, the value of the product itself will also increase, and the brand image will be well established as a relatively high-end positioning. Therefore, although this marketing strategy may have many shortcomings, it has brought more good effects to the brand as a whole for the business to improve the brand image and increase their sales and profit.
... Another recent development is the fact that decision making is increasingly taking place in online environments. As a result, there is now an increasing number of applied studies, in particular those investigating human decision making in online shopping environments [24][25][26][27]. ...
This paper explores consumer decision making, particularly focusing on the increasing prevalence of choices on the Internet such as online shopping. Examining the fundamental question of how individuals decide how to decide, our paper draws upon the effort–accuracy framework. This framework indicates that people typically consider both the cognitive effort associated with employing a specific decision strategy and the decision quality (i.e., accuracy) implied by using a particular strategy. However, decision strategies with high accuracy imply high effort. Empirical evidence shows that people often use decision strategies that require little effort. As a result, accuracy is often not high. Against this backdrop, this paper introduces a quantitative approach leveraging principal component analysis (PCA) as a decision support tool. Based on a simulation study, the approach demonstrates that it is possible to maintain high accuracy with significantly reduced effort in multi-attribute decision situations where attribute information is available in a quantitative format. This demonstration is based on the example of two decision strategies, which are both theoretically and practically highly relevant: the multi-attribute utility model (MAU) and the elimination-by-aspects strategy (EBA). By employing PCA for dimensionality reduction, the approach becomes particularly advantageous for online shops and online comparison portals, presenting users with concise yet accurate information. It is important to emphasize that our PCA approach is designed for data with a natural ordering, primarily focusing on quantitative variables. Consequently, decision situations where qualitative variables (e.g., product design or color) play a role in the decision-making process will need further exploration in future studies. However, we present a first solution to this problem so that our approach, based on this solution, can be implemented by online shops and online comparison portals in the near future.
... Although extant literature has investigated the impact of various factors, such as product features and consumer characteristics, on different perceptions of price, most of them focus on the impact of price on consumers' final purchases, ignoring the possible influence of decision-making stages. A series of prior studies have consistently proven that consumers may utilize different information and exist different psychological perceptions in different decision-making stages (Levin et al., 2005;Hubl and Trifts, 2000;Guo et al., 2012). Thus, it is worth exploring how consumers perceive price information and develop attitudes toward products at different decision-making stages. ...
E-commerce platforms generally provide consumers with the function of virtual shopping carts to help them store interested products. Although about 80% of online consumers intends to purchase after adding products to their shopping cart, the abandonment rate of cart products has been up to 70%. It is important to understand how to improve consumer attitude toward product both before and after cart use. Building on the relevant literature and the consumer shopping goal stages theory, this study aims to examine the effects of product price, as one of the most indispensable and important information in online shopping, on consumer attitudes toward product at different decision-making stages in online shopping (i.e., add-to-cart stage and place-an-order stage), and the mediating roles of perceived product quality and monetary sacrifice. The findings from behavioral experiment suggest that high price leads to a more positive attitude toward product at add-to-cart stage by strengthened perception of high product quality, while results in a less positive product attitude at place-an-order stage because of the enhanced perception of monetary sacrifice. Both theoretical contributions and practical implications are discussed.
... The greater the match between the information provided and that desired by the target audience, the more effective the information delivery becomes (Chaiken and Stangor 1987). Häubl and Trifts (2000) indicate that consumers who use recommendation services can find their desired product after examining an average of 6.6 items, whereas those who do not must examine approximately 11.7 items on average. Online recommendation systems predict consumer demand and interest by analyzing past data and providing recommended product information to assist consumers in making purchase decisions (Bobadilla et al. 2013). ...
A deeper understanding of purchase intentions within the unique context of real-time streaming platforms, on which consumers interact by exchanging opinions and recommending products, is required. Based on the stimulus-organism-response (SOR) theory, this study investigates the effect of real-time streaming on purchase intention for e-commerce products, which goes beyond traditional e-commerce platform research. The findings reveal that accuracy of product recommendation increases functional value and the streamers’ attractiveness enhances social value and immersion. Additionally, consumer-to-consumer (C2C) interactions elevate both social and functional values as well as immersion. Based on SOR theory, this study empirically extends the purchase intention model tailored to the unique context of streaming commerce. We include the roles and significance of streamers’ attractiveness and C2C interactions as variables to explain this context and provide a mediation mechanism for purchase intention. This study provides empirical evidence of the operational direction for the success of real-time streaming commerce platforms.
... Consumer purchase decisions refer to the ability of consumers to be willing to buy certain products (Dodds et al., 1991) The decision-making process of consumers is information processing (Bettman, 1979) Consumers find information, evaluate it and make choices (Bettman et al., 1998). Häubl & Trifts, (2000) suggest that consumers' decisionmaking process goes through five steps: (1) need recognition, (2) information search, (3) evaluation of alternatives, (4) purchase decision, and (5) post-purchase behaviour. ...
The rapid development of technology leads to diversification in consumer behavior. Businesses face greater competition challenges. New factors such as online customer reviews also affect consumer purchasing decisions. In order to create sustainable sales growth, businesses need to pay attention to the customer experience to reduce the percentage of customers switching to a new brand. This study incorporates these factors into the proposed model to assess their relationship. The analytical results show that the factors of customer online reviews and brand switching all impact purchase decisions.. Research is meant for businesses in general and marketers in particularly.
... This, in turn, assists customers in determining what to purchase and from whom [22]. The timeliness of decision-making is directly associated with online shopping behavior [21]. Thus, the proposed hypothesis is: H6: Decision-making skills have a positive relationship with financial behavior as perceived by customers. ...
Over the last ten years, financial technology, often known as fintech, has significantly driven major transformations in worldwide financial processes, reshaping the banking, investing, and payment sectors. This study examines the relationship between the various dimensions of digital financial literacy and customers’ financial behavior. Moreover, gaining insight into individuals’ perspectives, comprehension, and interaction with digital financial services would enable regulators and financial institutions to enhance their knowledge of consumers’ financial behavior. The methodology used for this study is an extensive review of current literature about digital financial literacy, consumer financial behavior, and the intersection of these areas. The review offers an extensive understanding of the existing research, pinpoints any gaps in the literature, and amalgamates essential findings to guide the development of a conceptual framework. The results of this review will enhance the current knowledge base, providing valuable insights for researchers. Policymakers should integrate digital financial literacy programs into comprehensive financial education campaigns to enhance the public's understanding of digital financial instruments and their consequences.
Agents help consumers make decisions. While agents have traditionally been human (e.g., sales associate, real estate agent, financial advisor), artificial intelligence (AI) agents are becoming more prevalent. We find that the type of agent, AI versus human, has an influence on intertemporal judgment. Specifically, when an agent is identified as AI, the concept of fast processing becomes more accessible, which makes time delays seem subjectively longer and encourages impatient behavior. These results have implications for how to conceptualize the influence of AI agents on judgment, the impact of time perception on intertemporal choices, and the sources of impatient behavior.
The rise of quick commerce has revolutionized the way consumers access and purchase products, characterized by rapid delivery times and a heightened sense of immediacy. This paper extensively delves into the crucial role of psychological factors that contribute to the success of q-commerce platforms, examining how consumer behavior is influenced by convenience, instant gratification, and cognitive biases.The research aims to detail the roles of psychological aspects that influence online consumer behavior.The findings suggest that q-commerce's success is not only a result of logistical innovation but also deeply rooted in fundamental psychological principles that satisfy consumers' desires for speed, simplicity, and the instant fulfillment of needs. Keywords : Psychological factors , Quick Commerce , Consumer Behaviour , Consumer influencing factors .
This study investigates the dynamics of Circular Economy (CE) practices in Small and Medium-sized Enterprises (SMEs), emphasizing their critical role in promoting sustainability. As we investigate the many implications on SMEs' adoption of CE, we pay special attention to the diverse consequences of internal and external stakeholder pressure. Furthermore, we underline the importance of positive managerial perceptions and offer a new perspective by viewing CE orientation as a mediating force. Our data collection was conducted in three phases using a survey methodology, yielding 196 responses from Estonian SMEs. The findings call into question the notion that stakeholder pressures are consistent, revealing varied influences on CE procedures. Significantly, increased CE orientation emerges as a driving element in improving organisational response to external stakeholder pressure. This study advances our understanding of the intricate relationships between stakeholder dynamics, managerial perceptions, and CE practices, providing valuable insights essential for SMEs to navigate the path towards sustainable practices. This study presents both theoretical and practical contributions and suggests avenues for future research to further explore the multifaceted nature of the relationships uncovered in this study.
La publicidad es una poderosa herramienta de comunicación que ha evolucionado a lo largo del tiempo para adaptarse a las necesidades y deseos de los consumidores. En este proceso, el uso del sonido ha tenido un papel crucial, especialmente en la era de la digitalización y la globalización. La imagen sonora, como un componente clave de las campañas publicitarias, crea una identidad única y memorable para las marcas, permitiendo a los consumidores asociar rápidamente los sonidos con los productos o servicios en cuestión. Este libro introduce al empleo de la música en publicidad, su relevancia y formas de implementación. Se presentan los diferentes aspectos que deben de tenerse en cuenta cuando se incorpora los elementos musicales al diseño de una campaña.
Mục đích của nghiên cứu này nhằm xác định và đo lường các yếu tố ảnh hưởng đến quyết định mua sản phẩm điện tử trực tuyến của người tiêu dùng tại Thành phố Cao Lãnh. Dữ liệu được thu thập 250 người tiêu dùng đã từng mua sản phẩm điện tử trực tuyến tại Thành phố Cao Lãnh. Phương pháp nghiên cứu định lượng gồm thống kê mô tả, đánh giá độ tin cậy thang đo, phân tích nhân tố khám phá và phân tích hồi quy tuyến tính bội được sử dụng để phân tích đo lường mức độ ảnh hưởng của từng nhân tố đến quyết định mua hàng điện trực tuyến của khách hàng. Kết quả cho thấy có 4 nhân tố ảnh hưởng đến quyết định mua sản phẩm điện tử trực tuyến cả người tiêu dùng bao gồm: nhận thức sự hữu ích, truyền miệng điện tử, sự tin cậy, giá cả hợp lý. Kết quả nghiên cứu này là cơ sở để xác định, định hướng và đưa ra giải pháp nhằm thúc đẩy quyết định mua sản phẩm điện tử trực tuyến của người tiêu dùng trong tương lai.
E-commerce applications have significantly changed how people transact with each other. This includes digital advances that drive illegal wildlife trade. In Indonesia, the Conservation Act of 1990 was enacted before the internet revolution and does not, therefore, adequately cover online illegal wildlife trade. In this study we identified wildlife traded illegally through advertisements published by five large national e-commerce companies and one social media platform operating in Indonesia, using 39 keywords. We also analysed data on wildlife cybercrime court case outcomes, associated criminal networks and their modus operandi. Over 12 months, we found 996 advertisements for wildlife and wildlife products, including of 45 nationally protected species, from 421 accounts. Amongst the six platforms monitored, Facebook Marketplace had the highest illegal wildlife trade traffic. We found that those prosecuted for online illegal wildlife trade were given low sentences. Our analysis of wildlife legislation, focus group discussions and expert interviews showed that the Government of Indonesia Trade Law (2014) and Law on Electronic Information and Transactions (2008) cannot be used to prosecute online illegal wildlife trade cases because these laws do not acknowledge regulations for protected species. Our study emphasizes the urgency of revising the Conservation Act and changing the definition of trade to include advertisements of protected species. We recommend development of screening tools for advertisements and accounts on e-commerce platforms, review of community/user guidelines to prohibit trade of protected species, and strengthening the approach of combining multi-context laws with stakeholder cooperation to prosecute online illegal wildlife trade cases.
Online platforms increasingly utilize technologies like artificial intelligence (AI)-empowered tools to reduce consumers’ search costs and simplify decision making. However, these tools often target specific types of information, leading to what we term "search cost reduction for partial information." Although designed to assist consumers, our study highlights their unintended consequence: these tools can induce "cognitive miser" behavior, where consumers focus on easily accessible information while neglecting other critical details. This behavior can ultimately result in poorer decision making. Using a natural experiment on Yelp, we evaluated the impact of its AI-powered image categorization feature, introduced in 2015 to reduce the search costs of review images. Through a difference-in-differences design and text analysis of consumer complaints, we found that this feature negatively affected decision quality. These findings carry important implications for platform managers and policymakers. Although search cost reduction tools can improve efficiency, they also risk biasing consumer attention toward easily accessible information at the expense of holistic decision making. Online platforms could mitigate these effects by complementing AI-empowered search cost reduction features with tools that emphasize information requiring greater cognitive effort, thereby ensuring balanced consumer awareness. We recommend that platform designers carefully evaluate the broader impacts of such tools to better support consumer decision making.
Introduction: The success of business models in India, such as e-tailing, transportation or online food ordering apps, despite any trend in GDP growth, needs to be evaluated in the context of technology adoption. This paper reviews the business model where small and medium restaurants align with delivery partners and payment gateways for successful coexistence. Objectives: The study aims to explore the dimensions of customer satisfaction of end users and job potential of individual delivery partners by probing whether customer satisfaction and job potential influence success of the online eatery business model and identifying whether success of online eatery business model impacts the benefits derived by participant eateries or restaurants. Theoretical Framework: The research is grounded in Customer Value and Satisfaction (CVS), which underpins the need of new business models that consider customer-supply strategies and continuous improvements as cornerstones of managerial effectiveness. The framework integrates theoretical perspectives that can help build typologies for business model innovation, explaining customer bliss, delivery partner benefits, and advantages for small eateries through partnerships for goals. Methods: A systematic literature review followed by a survey among 120 each of regular users of online food apps, delivery boys and restaurant partners from Kerala was conducted. Structural equation modelling was applied to identify the impact of end customer (diner) satisfaction and delivery partner (biker) benefit on the benefits to the eateries (restaurants). Results and Discussion: Findings reveal that the web support offered by online food apps through interfaces of apps and background support from restaurants had been influential on customer satisfaction. The results validate that customer satisfaction and job potential significantly predicts the success of business model and such success in partnerships for goals directly impacts the benefits derived by eateries. Research Implications: The theoretical and practical implications of this research are highlighted in the need for development of innovative technology and web interfaces that are more user-friendly. Policies should comprehensively integrate the service providers, logistics mechanism and end users. The results of the study if properly applied in eatery and online food delivery models can definitely influence practices in the field of e-businesses and online food delivery. Originality/Value: This study uniquely addresses the effective integration of supplier, logistic partner and final user for enriched customer satisfaction. The study contributes to the literature by highlighting the application of innovative partnership for goals in improved customer satisfaction.
Purpose
Esports game developers are incorporating interactive virtual shopping (IVS) experiences into their products to facilitate consumer–brand interactions. Despite the potential influence of IVS, existing research lacks an understanding of its impact on consumers’ overall affect– particularly game enjoyment, a critical factor in sustaining engagement with esports products – and on attitudinal change toward brands in the real world.
Design/methodology/approach
An experiment was designed to examine the impact of shopping in the virtually interactive esports marketplace on game enjoyment. Mediating effects of positive change in brand attitude, perceived realism and character attachment and the moderating effect of self-avatar gender congruity were investigated using SPSS PROCESS Macro. Additionally, the impact of brand popularity on the relationship between IVS and brand attitude was examined using analysis of covariance (ANCOVA).
Findings
There was a positive impact of IVS on game enjoyment, mediated by a positive change in brand attitude, perceived realism and character attachment. Self-avatar gender congruity moderated the mediation effect of perceived realism. Notably, less popular brands exhibited a greater change in brand attitude compared to more popular brands.
Originality/value
The findings add to the body of literature on esports, particularly in investigating the role of IVS within the esports virtual world and advancing research on cognitive appraisal theory. This study informs practitioners in the esports industry about the value of creating interactive virtual marketplaces, as they serve to benefit sponsoring brands and enhance game enjoyment for players.
Introducción: La realidad aumentada (RA) emerge como una tecnología revolucionaria en educación y marketing digital, que ha ganado relevancia por su capacidad de transformar la educación y el marketing digital, superponiendo información digital sobre el mundo real para crear experiencias interactivas. Este estudio revisa sistemáticamente la literatura para explorar su impacto y potencial transformador. Metodología: Esta revisión sistemática utiliza la metodología PRISMA para explorar aplicaciones, beneficios y desafíos de la RA. Resultados: Los resultados muestran que la RA en educación mejora el aprendizaje inmersivo y personalizado, mientras que en marketing digital aumenta la interacción y satisfacción del consumidor. Sin embargo, enfrenta desafíos tecnológicos y de adopción. Discusión: La RA transforma prácticas educativas y de marketing, pero necesita superar desafíos tecnológicos y de adopción para maximizar su efectividad. Conclusiones: La RA tiene un impacto transformador en educación y marketing digital, ofreciendo oportunidades significativas para mejorar el aprendizaje y la interacción del consumidor. Esta revisión sistemática destaca la necesidad de continuar investigando y desarrollando esta tecnología emergente.
The paper investigates the relationship between three terms: product packaging, promotional strategies, and consumer buying behavior. In today's competitive market, a lot of tactics are adopted by the marketers to attract the consumer as they focus on packaging and promotional strategies. The study investigates about different elements of packaging design and examines how they impact consumers' perceptions and preferences. As well as, it describes the effectiveness of promotional strategies in stimulating consumer purchasing behavior. Drawing upon theoretical frameworks and empirical evidence, this paper offers insights into how marketers can strategically utilize packaging and promotional techniques to enhance brand visibility, attract target audiences, and ultimately drive sales. Furthermore, it highlights the significance of understanding consumer psychology and market trends in devising successful packaging and promotional campaigns. For the study purpose, data have been gathered from various secondary sources. By comprehensively analyzing the interplay between product packaging, promotional strategies, and consumer behavior, this paper contributes to the existing literature on marketing and provides practical implications for businesses aiming to optimize their marketing efforts and achieve competitive advantage in the marketplace.
This paper discusses the way in which artificial intelligence technologies can combat counterfeit luxury goods and affect the behavior of consumers on the internet and market trust. E-commerce has opened up the opportunity for counterfeiting, resulting in economic damage to related industries and brand losses. Machine learning, natural language processing, image recognition, predictive analytics, among many other AI technologies, may help create deterrence against these activities. The paper investigates, within a systematic literature review, the role of AI in developing customer behavior analysis and market trust through Supply Chain Visibility (SCV) in terms of transparency and traceability. The findings here are
that AI considerably improves product verification, personalization, and trend prediction for fraud detection, marketing, and brand integrity. These technologies also support regulatory compliance while providing the consumer with more informed purchasing decisions, hence advancing knowledge of the role AI plays in guarding luxury markets and building trust.
This study examines consumer confusion and its impact on decision-making among female consumers in Indonesia's online cosmetics and personal care industry. With the rise of online shopping due to its convenience and extensive product information, consumer confusion—defined as the inability to correctly interpret various aspects of product information—has become a significant issue. A mixed-method approach was used, combining quantitative surveys and qualitative interviews. Data was collected through an online survey and analyzed using PLS-SEM, followed by semi-structured interviews that were manually coded through open, axial, and selective coding. The findings reveal that informational sources—overload, similarity, and ambiguity positively impact overall consumer confusion. Additionally, utilitarian decision-makers show higher levels of confusion compared to hedonic decision-makers. Previous brand experience was found to mitigate the negative effects of overload and ambiguity confusion on decision quality and enhance decision quality in the case of similarity confusion. Furthermore, overload and ambiguity confusion negatively impacts decision quality, whereas similarity confusion shows a positive impact. Finally, all informational sources of confusion positively impact decision postponement and cognitive dissonance. This study extends existing knowledge in marketing and consumer behavior, particularly regarding consumer confusion in the cosmetics sector. It offers practical insights for companies and brand managers to develop strategies that reduce consumer confusion, such as simplifying decision-making processes, providing clear product information, and leveraging previous brand experiences. These strategies aim to enhance decision quality, reduce decision postponement, and mitigate cognitive dissonance among consumers. Finally, the study suggests directions for future research in consumer confusion.
This study investigates the impact of brand authenticity (BA) on brand loyalty in the local footwear industry, using brand relationship quality as a mediating factor. Building on Lee and Chung's (2020) framework, the research identifies key attributes of brand authenticity (BA)—product authenticity, communication authenticity, brand originality, and price authenticity—and examines their impact on brand loyalty through brand relationship quality, specifically brand satisfaction, trust, and commitment. A mixed-methods approach was employed. The study first conducted a quantitative analysis using an online survey and PLS-SEM to examine the relationships between the brand authenticity attributes, brand relationship quality, and subsequently, brand loyalty. This was followed by qualitative semi-structured interviews, analyzed through thematic coding, to validate and elaborate on the quantitative findings and confirm the key BA attributes in the local footwear context. The study confirmed that product authenticity, encompassing design newness and product originality, enhances brand satisfaction, trust, and commitment. Communication authenticity, encompassing advertising authenticity and company authenticity, positively affects satisfaction and trust, while brand originality impacts satisfaction and commitment. Price authenticity enhances satisfaction and trust but does not significantly influence long-term commitment. The results indicate that brand satisfaction and commitment mediate the relationship between BA and brand loyalty, while brand trust does not. The research offers practical insights for local footwear brands to enhance authenticity and build stronger consumer relationships by focusing on original product designs, transparent communication, a distinctive brand story and image, and fair pricing practices. Theoretical implications include validating and adapting Lee and Chung's (2020) framework for the footwear industry, contributing industry-specific insights into the role of brand authenticity in shaping consumer loyalty within the local Indonesian footwear sector, guiding future research and brand management strategies.
In the digital era, where choices saturate daily life, the phenomenon of choice overload becomes a significant concern in consumer behavior and psychology. Recommender systems, exemplified by Netflix's sophisticated model, play a transformative role in navigating the vast landscape of digital entertainment. This qualitative study examines the impact of recommender systems on choice overload through 12 semi-structured interviews with Netflix users, revealing the intricate dynamics between personalization algorithms and user decision-making processes. The study is guided by the following research questions: (1) How does the Netflix recommendation system influence users' experiences of choice overload and ease of decision-making? (2) To what extent do users perceive Netflix's recommended content as appealing and diverse, and how reliant are they on these recommendations for content selection? (3) How do user interactions with Netflix's recommendation system, including user feedback, impact variables such as search time, choice effort, and choice satisfaction? The findings reveal a notable absence of explicit user feedback and the presence of choice overload in Netflix users. This is evident in prolonged search times, heightened choice effort, and moderate satisfaction levels, coupled with perceptions of unattractiveness and limited diversity in the recommended content. Negative emotional responses during content selection further underscore the challenges users face on the platform. Paradoxically, this gives rise to a potential “user's dilemma,” as the study exposes a high reliance and trust in recommendation lists. However, this reliance also results in users frequently experiencing frustration and disappointment when recommendations fail to meet expectations. The study provides valuable insights into the nuanced interactions between users and the Netflix platform and offers a foundational framework for ongoing refinement of recommender systems in the ever-evolving landscape of streaming services and emphasizes the need for recommendation lists to strike a delicate balance between effective guidance and user exploration.
Modern e-commerce websites often provide users with a variety of components, such as faceted filters and conversational recommender systems, that act as product advisors to help them find relevant products. However, these components are often treated separately and presented as independent components, leading to increased cognitive load and disruption in the search process. Also, the reasoning behind the resulting product recommendations is often not transparent. To address these limitations, we propose a novel approach that relies on a knowledge graph structure to seamlessly integrate faceted filtering and conversational advisors based on graphical user interfaces (GUI). Concretely, the knowledge graph is used to suggest filter values and products based on the user’s answers in the advisor, and, conversely, to determine follow-up questions based on the user’s selected filter values. The user interface also visualizes and explains the underlying relationships between answers given to the advisor and relevant product features in the filter component in order to increase the transparency of the search process. We conducted two user studies with a total of 448 participants to compare a system that integrates the different components according to our approach with a baseline system in which the mechanisms operate separately. Sequence analysis of the logged interaction data provided insights into participants’ behavior as they interacted with both systems. The results indicate that displaying recommended products and related explanations directly in the filter component increases acceptance and trust in the system. Also, the combination of a conversational advisor with values displayed in a filter interface, along with explanations of the underlying relationships, significantly contributes to the knowledge and understanding of those product features that are important in terms of the current search goal.
The study's focus is on the e-commerce sector, in particular how online merchants are affected by these characteristics and how other stakeholders, such as consumers or other market participants, perceive these factors. The focus of the study is e-retailing, which suggests that it is interested in the online sale of goods and services. This is a sizable and developing sector of the modern world economy. The phrase "Analyzing the Factors" implies that the research's goal is to recognize, investigate, and conceivably assess the many factors that affect or influence e-retailing.
Virtual reality (VR) has emerged as a transformative addition to real estate platforms, creating an interactive three-dimensional (3D) environment for consumers to explore property information, revolutionizing property presentation. Using a large-scale data set from a leading real estate platform, we demonstrate that VR serves as an efficiency enhancer rather than a market value influencer. Specifically, VR reduces a property’s selling time by 28%–49%, without influencing the selling price, challenging the conventional premise that VR may help increase selling price. Our further analysis highlights VR’s role as a provider of rich and credible information: our findings reveal that properties requiring greater effort to evaluate, those of higher quality, or where agent service is lacking, benefit most from the technique. Our work benefits property sellers by identifying which properties are more suitable for VR presentation and showing VR as a technological supplement when agent service is not satisfactory. Platforms can leverage the result to target sellers to apply VR, particularly when resources are limited. The acceleration effect of VR can benefit agents by allowing them to manage properties more efficiently and help platforms to build an efficient and sustainable market.
Over the past few years, the world of commerce has undergone lightning changes, both in terms of content and form, driven by the democratization of NICT usage. This transformation has led to the emergence of new behaviors, new players, new distribution concepts, and a new shopping experience. The presentation of the commercial offer has given rise to a new in-store experience for customers. The latter can be a source of satisfaction, and consequently of purchase intent. Considering the consumer as a being in search of a sensitive experience, phygital tools combined with experiential marketing have become an essential weapon used by companies to make consumers feel they are living a pleasant and unique experience, provoking in them a sense of belonging and loyalty.
Purpose
This research aims to examine the integral elements of omnichannel retailing, an evolving approach that blends online and offline shopping experiences. It focuses on how various factors – merchandise variety, monetary saving, personal interaction, complaint handling, social influence, perceived crowd and skepticism – affect relative advantage, consumer satisfaction and word-of-mouth (WOM) advocacy in an omnichannel context.
Design/methodology/approach
A comprehensive survey was conducted with 258 participants, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). This methodology provided insights into the complex relationships between different omnichannel retailing factors and their impact on customer satisfaction and WOM.
Findings
The study found that monetary saving influences both relative advantage and satisfaction. Personal interaction was observed to affect complaint handling and relative advantage. Importantly, relative advantage was found to impact both satisfaction and WOM. Additionally, the study highlighted the roles of social influence and satisfaction in enhancing WOM.
Originality/value
This research adds to the existing literature by providing a nuanced understanding of the dynamics of consumer engagement in omnichannel retailing. It bridges a gap in existing research by concurrently examining the impact of online and offline retail factors on consumer satisfaction and WOM in an omnichannel setting.
The role of effort and accuracy in the adaptive use of decision processes is examined. A computer simulation using the concept of elementary information processes identified heuristic choice strategies that approximate the accuracy of normative procedures while saving substantial effort. However, no single heuristic did well across all task and context conditions. Of particular interest was the finding that under time constraints, several heuristics were more accurate than a truncated normative procedure. Using a process-tracing technique that monitors information acquisition behaviors, two experiments tested how closely the efficient processing patterns for a given decision problem identified by the simulation correspond to the actual processing behavior exhibited by subjects. People appear highly adaptive in responding to changes in the structure of the available alternatives and to the presence of time pressure. In general, actual behavior corresponded to the general patterns of efficient processing identified by the simulation. Finally, learning of effort and accuracy trade-offs are discussed.
The authors examine the implications of electronic shopping for consumers, retailers, and manufacturers. They assume that near-term technological developments will offer consumers unparalleled opportunities to locate and compare product offerings. They examine these advantages as a function of typical consumer goals and the types of products and services being sought and offer conclusions regarding consumer incentives and disincentives to purchase through interactive home shopping vis-a-vis traditional retail formats. The authors discuss implications for industry structure as they pertain to competition among retailers, competition among manufacturers, and retailer-manufacturer relationships.
Reviews the literature showing the effects of task and context variables on decision behavior and evaluates alternative theories for handling task and context effects. These frameworks include (a) cost/benefit principles, (b) perceptual processes, and (c) adaptive production systems. Both the cost/benefit and perceptual frameworks are shown to have strong empirical support but unresolved conceptual problems. The production system framework has less direct support but has the desirable property of containing elements of both of the other frameworks. Research is discussed in terms of variables encountered by the decision maker: task complexity, response mode, information display, agenda effects, similarity of alternatives, and the quality of the option set. (91 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Notes that an accumulating body of research on clinical judgment, decision making, and probability estimation has documented a substantial lack of ability of both experts and nonexperts. However, evidence shows that people have great confidence in their fallible judgment. This article examines how this contradiction can be resolved and, in so doing, discusses the relationship between learning and experience. The basic tasks that are considered involve judgments made for the purpose of choosing between actions. At some later time, outcome feedback is used for evaluating the accuracy of judgment. The manner in which judgments of the contingency between predictions and outcomes are made is discussed and is related to the difficulty people have in searching for disconfirming information to test hypotheses. A model for learning and maintaining confidence in one's own judgment is developed that includes the effects of experience and both the frequency and importance of positive and negative feedback. (78 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The role of effort and accuracy in the adaptive use of decision processes is examined. A computer simulation using the concept of elementary information processes identified heuristic choice strategies that approximate the accuracy of normative procedures while saving substantial effort. However, no single heuristic did well across all task and context conditions. Of particular interest was the finding that under time constraints, several heuristics were more accurate than a truncated normative procedure. Using a process-tracing technique that monitors information acquisition behaviors, two experiments tested how closely the efficient processing patterns for a given decision problem identified by the simulation correspond to the actual processing behavior exhibited by subjects. People appear highly adaptive in responding to changes in the structure of the available alternatives and to the presence of time pressure. In general, actual behavior corresponded to the general patterns of efficient processing identified by the simulation. Finally, learning of effort and accuracy trade-offs are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Moderated multiple regression models allow the simple relationship between the dependent variable and an independent variable to depend on the level of another independent variable. The moderated relationship, often referred to as the interaction, is modeled by including a product term as an additional independent variable. Moderated relationships are central to marketing (e.g., Does the effect of promotion on sales depend on the market segment?). Multiple regression models not including a product term are widely used and well understood. The authors argue that researchers have derived from this simpler type of multiple regression several data analysis heuristics that, when inappropriately generalized to moderated multiple regression, can result in faulty interpretations of model coefficients and incorrect statistical analyses, Using theoretical arguments and constructed data sets, the authors describe these heuristics, discuss how they may easily be misapplied, and suggest some good practices for estimating, testing, and interpreting regression models that include moderated relationships.
Numerous models in the Management Science literature contain constructions that are a variant of the following: A decision-maker must choose from a set of alternatives based on imperfect information as to their relative quality, while further evaluation, through costly, provides more accurate information. We examine decision heuristics in which the optimal search policy entails a screening strategy limiting the number of alternatives in the subsequent, costly evaluation. There are two general methods for accomplishing this screening: Quota cutoffs operate by selecting the optimal number of alternatives to evaluate; Level cutoffs operate by specifying a minimally-acceptable level of the imperfect screening indicator. The present paper has three main objectives. First, to define the Level and Quota cutoff methods, broadly characterize optimal behavior for each and determine what aspects of the decision environment of order statistics as a methodology for exploring decision problems when information is imperfectly known; and third, to discuss the pivotal role of default, or fallback, options in a broad class of search problems. Quota and Level strategies restrict the number of alternatives passing the cutoff-based screen. Because restrictive cutoffs reduce evaluation costs while lowering the expected quality of the item finally selected, changes in the decision environment making the evaluation process less beneficial or increasing its cost drive the optimal cutoff to be more restrictive. In particular, increases in unit evaluation cost, improvement in the quality of a fallback option, decreases in the total number of alternatives available or improvement in the precision of the final evaluation process all lead to more restrictive cutoffs at optimum. These results hold over a remarkably broad range of assumptions and conditions. We also find that a better screening indicator leads to more restrictive screening when evaluation costs are low but, surprisingly, to less restrictive screening when costs are high. Comparing the two strategies, we find the unexpected result that the Quota cutoff strategy is generally superior to the Level, except under on of two fairly uncommon set of circumstances: when evaluation cost is prohibitively high, or when there is a fallback option of very high quality.
Individuals often use several different strategies such as the expected value rule, conjunctive rule, and elimination-by-aspects, to make decisions. It has been hypothesized that strategy selection is, in part, a function of (1) the ability of a strategy to produce an accurate response and (2) the strategy's demand for mental resources or effort. We examine effort and accuracy and their role in strategy selection. Several strategies that may be used to make choices under risk are simulated using a production system framework. This framework allows the estimation of the effort required to use the strategy in a choice environment, while simultaneously measuring its accuracy relative to a normative model. A series of Monte-Carlo studies varied several aspects of the choice environments, including the complexity of the task and the presence or absence of dominated alternatives. These simulations identify strategies which approximate the accuracy of normative procedures while requiring substantially less effort. These results, however, are highly contingent upon characteristics of the task environment. The potential of production system models in understanding task effects in decisions is stressed.
Using data on search and choice behavior from a local automobile market, we estimate monetary returns to search in terms of lower prices resulting from additional time invested in price search. For our analytical framework, we adapt a model developed in the job search literature to the problem of consumer search; this framework is especially useful for illuminating the relationship between time spent searching, the outcome of search, and demand and supply side variables. Our results indicate that, for this particular sample of buyers, marginal returns to search are broadly consistent with what one might expect if consumers balance costs and benefits of search, and that potential gains from additional search for lower car prices do not appear to be large for most consumers. Our study highlights many of the methodological difficulties involved in estimating returns to search, including isolating returns to different outcomes of search, and sensitivity of results to model specification and sampling error. We deal with these problems by trying to isolate time spent searching for price from other uses of search time, by deriving our model used in estimation from a specific conceptual framework, and by extensive specification testing.
In the last several years, the increased diffusion of computer andtelecommunications technologies in businesses and homes has produced newways for organizations to connect with their customers. These computermediated environments (CMEs) such as the World Wide Web raise new researchquestions. In this paper, we examine the potential research issuesassociated with CMEs in five areas: (1) decision processes, (2) advertisingand communications, (3) brand choice, (4) brand communities, and (5)pricing. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/47229/1/11002_2004_Article_138117.pdf
One of the main objectives facing marketers is to present consumers with information on which to base their decisions. In doing so, marketers have to select the type of information system they want to utilize in order to deliver the most appropriate information to their consumers. One of the most interesting and distinguishing dimensions of such information systems is the level of control the consumer has over the information system. The current work presents and tests a general model for understanding the advantages and disadvantages of information control on consumers' decision quality, memory, knowledge, and confidence. The results show that controlling the information flow can help consumers better match their preferences, have better memory and knowledge about the domain they are examining, and be more confident in their judgments. However, it is also shown that controlling the information flow creates demands on processing resources and therefore under some circumstances can have detrimental effects on consumers' ability to utilize information. The article concludes with a summary of the findings, discussion of their application for electronic commerce, and suggestions for future research avenues. Copyright 2000 by the University of Chicago.
A comprehensive theoretical framework for understanding consumers' information search behavior is presented. Unlike previous research, our model identifies not only what factors affect consumers' search behavior but also how these factors interact with each other. In particular, the model emphasizes the effect of prior brand perceptions on the search process. We argue that when consumers have brand-specific prior distributions of utility, the existence of relative uncertainty among brands is necessary for search to be useful. Thus, we explain why product class involvement or low search costs may not be sufficient to induce large amounts of search activity and why there may be an inverted-U-shaped relationship between search activity and experience. We test our theory on consumers' search behavior for new automobiles, using data collected contempraneously with consumers' actual decision process. Our data support our theory. Copyright 1997 by the University of Chicago.
This article examines the role of decision ambiguity in judgments that consumers make about an incumbent (the brand a consumer currently uses) versus an attack brand (a new, superior competitor). It is hypothesized that decision ambiguity creates an advantage for the incumbent. A conceptualization of decision ambiguity is offered. In three experiments, factors that can cause decision ambiguity are manipulated and their effects on preference for the incumbent are investigated. The results underscore the role of decision ambiguity in incumbent brand advantage. In two other experiments, boundary conditions are examined. Copyright 1995 by the University of Chicago.
If utility (net of price) varies by consumption occasion, the consideration set of a rational consumer will represent trade-offs between decision costs and the incremental benefits of choosing from a larger set of brands. If evaluating a brand decreases bias and uncertainty in perceived utility, the decision to evaluate a brand for inclusion in a consideration set is different from the decision to consider an evaluated brand. The decision to consumer is, in turn, different from the decision to consider. This article provides analytical expressions for these decision criteria and presents four aggregate implications of the model: (1) distributions of consideration set sizes, (2) order-of-entry penalties, (3) dynamic advertising response, and (4) competitive promotion intensity. Copyright 1990 by the University of Chicago.
Jn our article on information overload (Keller and Staelin 1987), we modeled the effect of two aspects of information-information quality (TQ) and information quantity (N)-on decision effectiveness, where decision effectiveness was defined in terms of normative utility. Results from an experiment we conducted were compatible with the model's implications and indicated that when everything else was held constant, increases in information quality (at least up to a point) and decreases in information quantity led to increases in decision effectiveness. In their comment, Meyer and Johnson (1989) consider how two biases might affect the interpretation of our experimental results. Specifically, they derive relationships between our two major design factors (i.e., TQ and N) and two factors that affect the analyst's ability to specify correctly which alternative a subject should choose as best from a pair of alternatives. The two factors Meyer and Johnson consider are task ease (TE*), defined as the absolute difference between the decision maker's true utilities for the two alternatives, and measurement error (Ei), defined as the difference between the decision maker's true utility (ut) and the researcher's measurement of this utility (ui).1 Using these relationships, they contend that our experimental results concerning the relationships between our two design factors, TQ and N, and the dependent measure of interest, decision effectiveness, may not be caused by the subject's inability to make good decisions. Instead, they contend that it is caused by the analyst's inability to correctly control for the variation of task ease and measurement error across the design. In this rejoinder to their comment, we summarize Meyer and Johnson's position on the two potential biases, and then explain why the bias associated with task ease was not a significant problem in our study. Furthermore, by quantifying the magnitude of the measurement error in our data and using the simulation methodology of Meyer and Johnson, we show empirically that, even though there probably was a bias due to measurement error, our general conclusions still hold. Finally, we summarize what we believe we have learned about information overload and suggest how one might design a study to avoid the potentially confounding bias due to measurement error.
Providing attribute information about alternatives can both help and hinder consumers evaluate products. We separate attribute information into two components: information quality and information quantity. We hypothesize, all else being equal, that the former component improves decision effectiveness while the latter component decreases decision effectiveness. The results of an experimental investigation designed to estimate the marginal effects of these factors were compatible with these premises. In addition, evaluations were also found to suffer in situations where high levels of information quality were made available. Insights into these and other observed effects are suggested after exploring the process by which subjects used the available information.
The Adaptive Decision Maker argues that people use a variety of strategies to make judgments and choices. The authors introduce a model that shows how decision makers balance effort and accuracy considerations and predicts which strategy a person will use in a given situation. A series of experiments testing the model are presented, and the authors analyse how the model can lead to improved decisions and opportunities for further research.
The authors examine how new brand entries affect consumers’ consideration sets. A within-subject longitudinal experiment examines several entry positions into existing markets. The results suggest that new brand entries produce changes in consideration sets toward dominating, compromise, and assimilated brands, away from extreme brands in two-brand markets, and toward dominating and away from extreme brands in eight-brand markets. These results are confirmed by a second experiment that utilizes a between-subject design and markets with six existing brands.
The performance of three formats in three choice sets was studied. In choice sets with negatively correlated attributes, the computer-assisted LINEAR format led to superior decisions in comparison with a computer-assisted CUTOFF format and a simple RAN DOM-order format. Decision quality, however, was high and the same across the formats in a choice set with non-negatively correlated attributes. The LINEAR format was highly regarded by subjects, resulted in timely decisions, and is recommended on the basis of its performance in the study.
Designing effective marketing programs requires forecasting the choice strategy a consumer will use in a given decision environment. Both simplifying and optimizing considerations may affect the strategy used. This study found individuals' perceptions of different strategies as simplifiers and optimizers varied, with number of options being reviewed operating as a moderator.
The authors examine how new brand entries affect consumers' consideration sets. A within-subject longitudinal experiment examines several entry positions into existing markets. The results suggest that new brand entries produce changes in consideration sets toward dominating, compromise, and assimilated brands, away from extreme brands in two-brand markets, and toward dominating and away from extreme brands in eight-brand markets. These results are confirmed by a second experiment that utilizes a between-subject design and markets with six existing brands.
The performance of three formats in three choice sets was studied. In choice sets with negatively correlated attributes, the computer-assisted LINEAR format led to superior decisions in comparison with a computer-assisted CUTOFF format and a simple RANDOM-order format. Decision quality, however, was high and the same across the formats in a choice set with non-negatively correlated attributes. The LINEAR format was highly regarded by subjects, resulted in timely decisions, and is recommended on the basis of its performance in the study.
Decision theory and research have focused almost exclusively on choice—the selection of the best option from a choice set containing two or more options. Largely overlooked is the question of how those particular options got there in the first place—why them and not others? This article describes a theory, called image theory, about how prechoice screening of options governs the contents of the set from which a choice is made and summarizes empirical tests of the theory. The research results suggest that screening plays a far more important role in decision making than is generally appreciated and that our view of decision making must be broadened accordingly.
Information displays influence decision processes by facilitating some decision strategies while hindering others. Component characteristics of displays, such as the form, organization, and sequence of information, influence decision processes through an adaptive mechanism whereby a decision maker balances the desire to maximize accuracy against the desire to minimize effort. Variations in the information display lead to changes in the anticipated effort and anticipated accuracy of each available strategy and, therefore, provide an incentive for decision makers to use different decision processes. Research in this area can provide guidance regarding the use of displays and other decision-aiding approaches.
The authors develop a model of consideration set composition. The approach taken is to compare the marginal expected benefits of including an additional brand in the consideration set with its associated costs of consideration. From an expression of the utility that a brand needs to gain membership in an existing consideration set, the authors derive an expression for set composition and optimal set size. They develop a measurement method to test the model at the individual level and apply it to the ready-to-eat cereal market. The model is tested in two ways. First, the utility function is calibrated at the individual level and the model is used to predict consideration of existing brands. The calibrated model also is used to forecast individual consideration of three new product concepts. Second, the predictive ability of a two-stage model of consideration and choice is tested against a traditional one-stage choice model. The authors conclude with a discussion of management implications of the model in terms of auditing currently available brands and new product management.
This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of
estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions
about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations
yet they reduce to the score equations for niultivariate Gaussian outcomes. Asymptotic theory is presented for the general
class of estimators. Specific cases in which we assume independence, m-dependence and exchangeable correlation structures from each subject are discussed. Efficiency of the pioposecl estimators
in two simple situations is considered. The approach is closely related to quasi-likelihood.
When unit prices were posted on separate shelf tags in a supermarket, consumer expenditures decreased by 1%. When unit prices were displayed also on an organized list, consumer savings were 3%. In addition, the list format caused a 5% increase in the market shares of store brands. The benefits to both consumers and retailers justify the cost of providing unit price information on a widespread basis.
Introduction, 99. — I. Some general features of rational choice, 100.— II. The essential simplifications, 103. — III. Existence
and uniqueness of solutions, 111. — IV. Further comments on dynamics, 113. — V. Conclusion, 114. — Appendix, 115.
Software agents help automate a variety of tasks including those involved in buying and selling products over the Internet. This paper surveys several of these agent-mediated electronic commerce systems by describing their roles in the context of a Consumer Buying Behavior (CBB) model. The CBB model we present augments traditional marketing models with concepts from Software Agents research to accommodate electronic markets. We then discuss the variety of Artificial Intelligence techniques that support agent mediation and conclude with future directions of agent-mediated electronic commerce research.
Rapid advances in information technology have brought decision makers the mixed blessing of an increasingly vast amount of easily available data. Designers of decision support systems (DSS) have focused on incorporating the latest technology with little attention to whether these new systems are compatible with the psychology of decision makers. Our premise is that DSS should be designed to take advantage of the distinctive competencies of decision makers while using technology to compensate for their inherent weaknesses. In this study we apply this approach to a forecasting task. We find that to arrive at a forecast decision makers often search their experience for a situation similar to the one at hand and then make small adjustments to this previous situation. Our theoretical model of the performance of this intuitively appealing strategy shows that it performs reasonably well in highly predictable environments, but performs quite poorly in less predictable environments. Results from an experiment confirm these predictions and show that providing decision makers with a simple linear model in combination with a computerized database of historical cases improves performance significantly. We conclude by discussing how these results can be used to help improve forecasting in applied contexts, such as promotion forecasting in the retail grocery industry.
This paper describes, summarizes and comments on the empirical studies in the use of three information technologies to support managerial activities: decision support systems (DSS), group decision support systems (GDSS), and expert systems (ES). These are collectively labelled as managerial support systems (MSS). A classification scheme to organize empirical research in MSS is proposed. An overview of empirical work on two major research themes, namely MSS “design” and “effects of use” of MSS, is then presented for the years 1981–1988. Following this overview, the research strategies suitable for empirical research in MSS are discussed. The paper concludes with suggestions about future research directions in the field.
We examine the effort required to execute decision strategies and propose a set of elementary information processes (EIPs) (e.g., reads, additions, comparisons) as a common language for describing these strategies. Based upon these component processes, a model for measuring the effort required to execute a decision strategy is proposed which suggests that effort is a weighted sum of EIPs. We test several variants of this model by attempting to predict decision latencies and subjective reports of effort. The proposed weighted EIP model provides good predictions for response time and subjective effort, and estimates of the time and effort associated with each EIP seem plausible and consistent with those found in other cognitive tasks. The time and effort required by each EIP do not vary substantially across rules; however, there are significant individual differences. On balance, the EIP approach to conceptualizing and measuring the effort of executing a choice strategy receives strong support.
The capabilities provided by decision support systems (DSS) can have a significant impact on the usefulness and satisfaction provided by a DSS. A questionnaire was sent to nonacademic members of the Institute of Management Sciences in an effort to identify characteristics and capabilities common to DSS. Analysis indicated that five different categories of DSS could be identified. Each of these categories provided the DSS user with a unique set of capabilities ranging from simple data retrieval to a fully integrated DSS. Analysis also indicated that the five DSS categories identified in this study mapped easily onto Alter's DSS taxonomy. By utilizing Alter's taxonomy and the results obtained in this study, the DSS builder is provided a starting point for the development of future DSS.
The traditional assumption in the decision support systems (DSS) literature is that if decision makers are provided with expanded processing capabilities they will use them to analyze problems in more depth and, as a result, make better decisions. Empirical studies investigating the relationship between DSS and decision quality have not borne this out. The explanation for such outcomes could be found in behavioral decision-making theories. The literature on behavioral decision making indicates that the conservation of effort may be more important than increased decision quality in some cases. If ths is so, then the use of a decision aid may result in effort savings but not improved decision performance. The two experiments reported here use verbal protocol analysis to compare the extent of information use by unaided decision makers and users of a decision aid designed to support preferential choice problems. The results of the two studies indicate that subjects with a decision aid did not use more information than those without one. Overall, subjects behaved as if effort minimization was an important consideration. For DSS researchers these studies indicate that to understand the DSS-decision quality relationship, it is necessary to consider the decision maker's tradeoff between improving decision quality and conserving effort. For DSS designers these results imply a need to focus on the moderating role that effort will play in determining DSS effectiveness.
Management is communication intensive and, therefore, managers may derive benefits from computer-based alternatives to the traditional communication modes of face-to-face (FTF), telephone, and written memo. This research examined the use of electronic messaging (EM) by ongoing management groups performing a cooperative task. By means of an in-depth multimethod case study of the editorial group of two daily newspapers, it examined the fit between the interactivity of the chosen communication mode (FTF vs. EM) and the mode of discourse it was used for (alternation vs. interaction/discussion). Two propositions were derived from this exploratory study. The first proposes that FTF, being highly interactive, is appropriate for building a shared interpretive context among group members, while CMC, being less interactive, is more appropriate for communicating within an established context. Groups exhibiting effective communication will use FTF primarily for interactive discourse and EM for discourse consisting primarily of alternating adjacency pairs. The second proposes that to the extent that the appropriate communication modes are chosen, communication will be more effective.
A theory is proposed for designing decision support systems (DSS) so that the confidence a decision maker has in a decision made using the aid equals the quality of that decision. The DSS design theory for user calibration prescribes properties of a DSS needed for users to achieve perfect calibration. Relevant calibration, decision making, and DSS literatures are synthesized; and related behavioral theories are borrowed to identify the properties of expressiveness, visibility, and inquirability as requisite components of the DSS design theory for user calibration.
Introduction, 99.--I. Some general features of rational choice, 100.--II.
The essential simplifications, 103.--III. Existence and uniqueness
of solutions, 111.--IV. Further comments on dynamics, 113.--V. Conclusion,
114.--Appendix, 115.
A theory and methodology are developed for explicitly considering the cost of comparing diverse choice alternatives. The theory allows (1) explicit analytical measures of the cost of using various simplified decision strategies, and (2) predictions regarding the distribution of mistakes a consumer is likely to make when reducing decision-making effort.
This article focuses on memory-based choice situations where changes in a brand's accessibility may affect the probability that it is retrieved and considered for choice. In such instances, factors other than evaluation may affect which brands are brought to mind at purchase. Two experiments are described that manipulate the determinants of brand accessibility and measure consequent effects on retrieval, consideration, choice, and evaluation. Results provide evidence for the influence of memory during the brand-choice process. For a brand to be selected in memory-based choice, the consumer must recall that brand and fail to recall other brands that might otherwise be preferred. Copyright 1990 by the University of Chicago.
Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.
The need to support individuals in the implementation of their decision-making strategies has often been articulated. However, computerized decision support addressing this need is conspicuous by its absence. We argue that this lack is a consequence of the dearth of theoretical guidance for the derivation of practical design guidelines. This paper, utilizing research in psychology and cognitive engineering, attempts to fill this theoretical gap. A laboratory experiment testing the utility of a DSS incorporating the derived design guidelines is described. Results indicate that itispossible to incorporate implementation support into DSS, that such support increases decision making efficiency and effectiveness, and that need as well as usefulness of such support increases with the level of complexity of the decision strategy.
This paper examines the role of computer-based decision aids in reducing cognitive effort and therefore influencing strategy selection. It extends and complements the works reported in the behavioral decision theory literature on the role of effort and accuracy in choice tasks. The central proposition of this paper is that specific features can be incorporated within a set of decision aids that will alter the effort required to implement a particular choice strategy relative to other strategies, and that this will influence strategy selection by the decision maker. In a laboratory experiment, using a repeated measures design, 48 subjects performed a preferential choice task using different decision aids. Subjects were given different levels of support to reduce the cognitive effort associated with different preferential choice strategies. In particular, the decision aids provided varying levels of support for the processing associated with either elimination by aspects or additive difference strategies. The study examined how information processing strategies were influenced by the decision aids. The results show that decision aids which reduce the effort associated with the elimination by aspects strategy induce behaviors associated with elimination by aspects. More importantly, there was an interaction effect caused by the distinct behavior of the group which was provided support for additive difference but not for elimination by aspects. This group processed the information about available choices in a way that is consistent with an additive difference strategy. These findings indicate that a decision aid can induce additive processing by altering the relative effort requirements of different choice strategies.
Preference reversals occur when a decision maker prefers one option to another in one response mode but reverses that ordering when preferences are elicited in another response mode. We report the results of two experiments which significantly impact the frequency of preference reversals. Specifically, when the probabilities are displayed in a format which appears harder to process, the frequency of reversals is increased. Process-tracing evidence suggests that decision-makers also shifted information processing strategies as a function of information format. We discuss the implications for theories of preference reversals and strategy selection, and for the design of information displays.
Information systems can serve as intermediaries between the buyers and the sellers in a market, creating an "electronic marketplace" that lowers the buyers' cost to acquire information about seller prices and product offerings. As a result, electronic marketplaces reduce the inefficiencies caused by buyer search costs, in the process reducing the ability of sellers to extract monopolistic profits while increasing the ability of markets to optimally allocate productive resources. This article models the role of buyer search costs in markets with differentiated product offerings. The impact of reducing these search costs is analyzed in the context of an electronic marketplace, and the allocational efficiencies such a reduction can bring to a differentiated market are formalized. The resulting implications for the incentives of buyers, sellers and independent intermediaries to invest in electronic marketplaces are explored. Finally, the possibility to separate price information from product attribute information is introduced, and the implications of designing markets promoting competition along each of these dimensions are discussed. Copyright 1997 by The Institute of Management Sciences Keywords: electronic markets, search costs, consumer search, electronic commerce, Internet markets 1.