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This study presents one of the earliest empirical investigations on how brand chatbots' anthropomorphic design and social presence communication strategies may improve consumer evaluation outcomes via the mediators of parasocial interaction and perceived dialogue.

This study employs a 2 (high vs. low social presence communication) by 2 (anthropomorphic vs. non-anthropomorphic bot profile) between-subject experimental design to evaluate how chatbots' high social presence communication and anthropomorphic profile design may enhance perceptions of parasocial interactions and dialogue with the chatbot, which in turn drive user engagement, interaction satisfaction and attitude toward the represented brand.

The influences of chatbots' high social presence communication on consumer engagement outcomes are mediated by perceived parasocial interaction and dialogue. Additionally, chatbots' anthropomorphic profile design can boost the positive effects of social presence communication via the psychological mediators.

This study advances the interactive marketing literature by focusing on an emerging interactive technology, chatbots. Additionally, distinct from prior chatbot studies that focused on the utilitarian use of chatbots for online customer support, this study not only examines which factors of chatbot communication and profile design may drive chatbot effectiveness but also examines the mechanism underlying the messaging and design effects on consumer engagement. The findings highlight the mediating role of interpersonal factors of parasocial interaction and perceived dialogue.

The purpose of this paper is to describe UWIRS (Ubiquitous Web Information Retrieval Solution), an agent‐based Web Information Retrieval (WIR) solution designed taking into account the unique features of the World Wide Web (WWW) and the limitations of existing WIR solutions for ubiquitous environments.

UWIRS can offer recommendation services by using the Multi‐Agent Vizier Recommendation Framework (Vizier). Vizier was designed under a generic approach and therefore can provide services to information retrieval applications so these may offer product recommendations that consider several adaptation/personalization dimensions (e.g. user dimension, context, among others).

Overall, the main challenge resides on: location, retrieval, integration and presentation of information from the WWW, quickly and accurately, to satisfy a user's singular information needs.

In UWIRS, agents cooperate in order to retrieve personalized information, considering user needs, goals, preferences and contextual features. UWIRS's agents are responsible for: interpreting user input and adding adaptation information by means of a query enrichment process; identifying and selecting the appropriate data sources taking into consideration the Profile Set (composed of User, Device and Information‐Provider Profiles); executing query routing and the information retrieval process; integrating and filtering the retrieved results; and lastly, coherent presentation of quality and relevant ubiquitous information (anytime, anywhere and anyhow) that satisfies the user's particular information needs and constraints associated to his/her access device.

The current increase in social media activity related to brand–consumer interactions is progressively influencing the manner in which brands and their customers communicate. Whereas this attention to social media is warranted, researchers and brand managers must also recognize that consumers connect and engage with brands across other communication platforms as well. Accordingly, this study aims to examine brand–consumer interactions taking place across social, online and physical platforms, as well as consumer motives for initiating these brand interactions across various platforms.

A mixed-method approach integrating quantitative and qualitative data was used. We administered a written diary to 102 individuals over a two-month period, in which study participants recorded their motivations and platform use in their interactions with a brand. We evaluated latent-class mixture models for complex data and multi-level latent-class mixture models to identify classes of interactions based on participants’ motivations and platform use as well as customer segments based on the identified motives-by-platform classes.

The findings reveal ten categories of motives for interacting with brands, including promotions and incentives, timely information, product information, engagement, browsing, purchase, customer service, branded content, entertainment, and personalization/exclusivity. Furthermore, six motives-by-platform interaction classes are identified. The findings suggest three consumer segments differentiated by their motives-by-platform profiles.

This study adds to past research investigating the motives behind brand–consumer interactions in social media by investigating both social media and non-social media-related interactions, and offering a typology of interaction profiles that considers interaction motives and platform preferences.

This study illustrates that consumers are driven to interact with brands based upon the ten motive categories. These motives, in turn, are associated with different platform uses. Thus, it is important for brands to adopt ambidexterity across multiple communication platforms.

This research adds to the understanding of brand–consumer interactions conducted on online and offline communication platforms.

The purpose of this paper is to predict tie strength using profile similarities and interaction data between users, and thus distinguish between strong and weak relationships on social network sites (SNSs).

This study developed a program and an online questionnaire to collect the data set from Facebook, and then integrated that data set with a subjective data set consisting of participants’ opinions of the strength of their friendships on Facebook. The model developed here for predicting tie strength performed well when was applied on a data set of 6,477 SNSs’ ties, distinguishing between strong and weak ties with over 50 percent accuracy.

The results developed an algorithm (predictive model) that quantifies and measures tie strength continuously to bridge the gap between theory and practice. The results found that the variables in the dimension of emotional intensity had stronger effects than other interaction variables.

This study developed a predictive model that helps explain the meaning of interaction on SNSs, providing an efficient method to examine tie strength on SNSs. The tie strength estimates can also be used to improve the range and performance of various aspects of SNSs, including link predictions, product recommendations, newsfeeds, people searches, and visualization. Such understanding of the structure of SNSs might lead ultimately to the design of algorithms that can detect trusted or influential users of SNSs.

This research provides a new perspective on the long-standing debate of open-plan versus cellular offices. It analyzes the effects of workplace layouts on organizational outputs such as innovation, efficiency and privacy by considering the physical space of an organization alongside its organizational structure. This socio-spatial approach draws on correspondence theory originating from space syntax to understand the potential for unplanned encounters between diverse groups of people.

Three different organizations are studied, two open-plan and one cellular office. Floor and seating plans are analyzed to calculate the degree of correspondence between the spatial and conceptual closeness of people. Demands for each organization are derived from semi-structured interviews and publicly available information.

The three studied organizations present very different degrees of openness toward others in ways that challenge conventional views of cellular and open-plan offices. In each case, the degree of correspondence matches the demands placed on the organization, and hence, providing a relatively good fit between the organization and interior environment.

A larger sample of open-plan and cellular offices would be useful to consider in further research.

Managers can use the concept of correspondence to generate the appropriate degree of unplanned encounters between the right sets of people in order to achieve the best organization-environment fit.

The main innovation of this paper lies in its socio-spatial approach, considering physical space alongside managerial, organizational choices.

The digitalization process has been influential on the way marketing is conducted. However, luxury brands have not yet fully channeled the benefits of the integration of various touchpoints. The aim of this chapter is to provide insights into building a luxury fashion omnichannel strategy through the integration of online and offline consumer journeys, based on the emerging needs and lifestyles of different luxury consumer segments. Accordingly, exploratory research is designed to understand luxury consumer typologies and luxury fashion shopping journeys. In-depth interviews were conducted for data collection in Istanbul, with 16 participants. Grounded theory coding was used for analyzing the data. Findings revealed four-consumer typologies –Luxury Beginners, Nouveaux Riches, Conservatives, Established Luxury Consumers. Luxury fashion journey map covering three major steps – pre-purchase, purchase, and post-­purchase – was illustrated based on the usage of both digital and non-digital channels and agents through the journey with discussions to present consumer differences. The results of the study add to the current literature and provide an omnichannel roadmap for the practitioners.

To avoid (costly) conflict, it is imperative to uncover when negotiators cooperate. The previous study has shown that negotiators’ cooperative or competitive behavior is oftentimes guided by cues about their counterpart; information about his/her traits or behavior. Using regulatory focus theory, this paper aims to investigate when this is likely to happen. The authors hypothesize and test that because prevention focus (rather than promotion focus) is associated with concerns for safety and concrete surroundings, it strengthens the impact of counterpart cues.

The authors used two scenario studies and one behavioral negotiation study to test the general hypothesis. The authors measured or manipulated participants’ regulatory focus, manipulated counterpart cues by varying the information negotiators received about their counterpart’s traits and behavior, and measured participants’ cooperative or competitive concession making behavior.

Results from the studies confirmed that under prevention focus, negotiators’ cooperative behavior depended on whether they received cooperative versus competitive counterpart cues more than under promotion focus. Furthermore, results also showed that under prevention focus, negotiators’ behavior was relatively unaffected by their own social motivation – i.e. their personal goal to obtain favorable outcomes for oneself or for both negotiation parties.

By showing that regulatory focus determines when counterpart cues affect negotiation behavior, this paper furthers the understanding of when contextual factors affect negotiators' behavior. In addition, it contributes to the understanding of the complex effects of prevention focus in interpersonal behavior.

This paper aims to focus on collaborative consumption, that is, the peer-to-peer (P2P) exchange of goods and services facilitated by online platforms. Anchored in the access paradigm, collaborative consumption (e.g. accommodation rental and ridesharing services) differs from commercial services offered by firms (e.g. business-to-customer [B2C] carsharing). The aim of this study is to examine the nuanced styles of collaborative consumption in relation to market-mediated access practices and socially mediated sharing practices.

Following the general research trend on mobility services, the context of long-distance ridesharing is chosen. Data collection was conducted using participant observation as peer service provider, 11 ethnographic interviews of consumers and a netnographic study of digital artifacts.

Using practice theory, ten ridesharing activities were identified. These activities and the nuances in the procedures, understandings and engagements in the ridesharing practice led to the distinction of three styles of collaborative consumption: communal collaborative consumption, which is when participants seek pro-social relationships in belonging to a community; consumerist collaborative consumption, performed by participants who seek status and convenience in the access lifestyle; and opportunistic collaborative consumption, when participants seek to achieve monetary gain or personal benefits from abusive activities.

By taking a phenomenological approach on collaborative consumption, this study adds to the understanding of the sharing economy as embedded in both a utilitarian/commercial economic system and a non-market/communal social system. The three styles of collaborative consumption propose a framework for future studies differentiating P2P exchanges from other practices (i.e. B2C access-based services and sharing).

This study aims to investigate the relationship between material properties and alloying elements of carbon steels through predictive modeling. Aircraft control cables are usually made of steel materials and subjected to deformation because of the motion of control surfaces such as aileron, rudder, elevator and trailing edge flaps. Investigation of the relationship between material properties and alloying elements would therefore be explored.

This study is focused on the modeling of mechanical properties of carbon steels concerning the content of alloying elements by using response surface methodology with false discovery rate (FDR) correction approach. SAS Institute JMP data analysis software was used to develop response and argument relationships in various carbon steels without including thermomechanical treatment effect. Mechanical properties were considered as tensile strength, yield strength, ductility, and Brinell hardness. Carbon (0.28 Wt.%-0.46 Wt.%) and manganese (0.7 Wt.%-0.9 Wt.%) proportions were gathered from ASM Handbook. Linear regression models were tested for the statistical adequacy by using analysis of variance and statistical significance analysis. A posterior probability, which refers to Benjamini–Hochberg FDR (BH-FDR), was embedded as multiple testing corrections of the t-test p-values.

Predictive modeling of the material properties for aircraft control cables was successfully achieved by using the response surface method with BH-FDR significance level of 0.05.

The effect of statistically developed graphical interactions of alloying elements on the common mechanical properties of such steels would provide prompt comparison to material suppliers and part manufacturers except those subjected to thermomechanical treatment applications.

The present chapter expands on recent research demonstrating an empirical link between theoretical constructs within affect control theory (ACT) and expectation states theory. I explore the utility of a joint application of the two theories, employing simulated interactions to examine status organizing processes.

Although simulation results do not constitute data by which theoretical claims can be tested, they are useful for developing new research questions. I report results from a series of simulated dyadic interactions using ACT’s Interact program to investigate potential emotional and identity processes that underlie the enactment of status differences, and to explore affective responses to the legitimation and delegitimation of status orders.

Simulation results call attention to a dynamic interplay between structural elements of the situation and the agentic behavior of interactants, suggesting that behavioral attempts to reduce deflections may lead to shifts in expectations over the course of interaction. Results raise the possibility that differences in affective impressions may produce expectations that are initially asymmetrical between interaction partners. Further, results suggest that the standardized tasks commonly employed in expectation states research may unintentionally generate affective responses that encourage status convergence.

Drawing on insights and methods from ACT, expectation states researchers can improve the scientific understanding of small group interaction. Employing simulated interactions, researchers can promote theoretical advancement by uncovering new lines of inquiry at the intersection of two prominent social psychological traditions. Simulations also provide a further tool for methodological refinement within the standardized experimental setting.