Extending the Boundaries of Supply Chain Transparency: Supplier Monitoring Activity Disclosure, Consumer Evaluations, and Brand Equity

Socially responsible policy makers and consumers are pressuring firms to make their supply chains more transparent by disclosing information about their supplier monitoring activities (SMA). Yet, high monitoring costs and the complexity of supply chains pose challenges for firms to effectively monitor their extended supply chain, including both first-tier and lower-tier suppliers. In order to comprehensively evaluate the net benefit from SMA, it is therefore critical to consider potential effects on drivers of additional revenues that may accrue from the disclosure of SMA to consumers. Prior research on SMA has examined the associated cost, risk, and supplier relational implications on the focal firm. I examine the effect of supply chain transparency by means of a firm’s SMA disclosure on consumer evaluations through a series of experiments and sentiment analysis of social media data. Further, I study the effect of SMA disclosures on a firm’s brand equity via content analysis of corporate social responsibility (CSR) reports. Specifically, I investigate the effects of (1) mere disclosure of SMA, (2) the breadth of SMA, the depth of SMA, and the specific mechanism used to monitor lower-tier suppliers, and (3) the interactions between issue involvement, SMA disclosure, and SMA characteristics on consumer evaluations. The results reveal that (1) the disclosure of SMA information improves individual-level consumer evaluations, consumer sentiment, and organizational-level brand equity; (2) SMA characteristics including breadth, depth, and monitoring mechanism each have effects on consumer evaluations; and (3) consumers’ CSR involvement plays an important role in strengthening the relationship between firms’ SMA disclosures and evaluations. This work makes several important contributions to several literature streams including the CSR literature, the supply chain transparency literature, and the sustainable supplier management literature. This research also provides motivation and guidance for practitioners that engage in or are considering SMA by highlighting SMA disclosure as a means for firms to boost consumer evaluations. Further, for firms that strive to achieve supply chain transparency through SMA disclosures, results show that not only is it critical to understand what to disclose, but also to whom to disclose

Humanize your business. The role of personal reputation in the sharing economy

Drawing on the services marketing and sharing economy literature, the study identifies the leading reputational attributes that boost popularity in sharing economy platforms. As popularity stands as a purchase decision-making tool, the purpose of this paper is to jointly examine the influence of personal reputation and product description. A sample of Airbnb listings was collected in November 2016 in Italy and UK (n = 502). The database consists of popularity variables along with personal reputational attributes and the description of the product being offered. The findings of the study, based on the Shapley Value Regression, suggest that personal reputation is of paramount importance, explaining alone almost 40% of popularity variation. The paper concludes with theoretical implications on self-branding and, given the importance weights of the different attributes in popularity building, practical implications for sellers operating in sharing economy platforms

The Consequences of Participating in the Sharing Economy: A Transparency-Based Sharing Framework

The sharing economy is estimated to add hundreds of billions of dollars to the global economy and is rapidly growing. However, trust-based commercial sharing—the participation in for-profit peer-to-peer sharing-economy activity—has negative as well as positive consequences for both the interacting parties and uninvolved third parties. To share responsibly, one needs to be aware of the various consequences of sharing. We provide a comprehensive, preregistered, systematic literature review of the consequences of trust-based commercial sharing, identifying 93 empirical papers spanning regions, sectors, and scientific disciplines. Via in-depth coding of the empirical work, we provide an authoritative overview of the economic, social, and psychological consequences of trust-based commercial sharing for involved parties, including service providers, users, and third parties. Based on the aggregate insights, we identify the common denominators for the positive and negative consequences. Whereas a well-functioning infrastructure of payment, insurance, and communication enables the positive consequences, ambiguity about rules, roles, and regulations causes non-negligible negative consequences. To overcome these negative consequences and promote more responsible forms of sharing, we propose the transparency-based sharing framework. Based on the framework, we outline an agenda for future research and discuss emerging managerial implications that arise when trying to increase transparency without jeopardizing the potential of trust-based commercial sharing

Developing a Parasocial Relationship with Hotel Brands on Facebook: Will Millennials Differ from GenXers?

Facebook, particularly its brand page, is becoming one of the most powerful tool for relationship building and customer engagement for hospitality companies. As the social media marketing practices evolve in the hospitality industry, the industry starts to realize the importance of customer participation behaviors based on relationship quality rather than quantity of interactions and the rising significance of the Millennials generation. To respond to this trend, this study pursues an empirical investigation of the antecedents for consumer-hotel brand relationship on Facebook, and the potential differences between Millennials and non-Millennials, particularly the GenXers. It also examines the potential varying relational consequences on consumers\u27 online participation behaviors and brand loyalty between these two groups. More specifically, this study positions Facebook as an innovative communication medium, and applies the “parasocial relationship” framework in mediated communication literature as an overarching theoretical guide. Five social-media related factors are included to explain the psychological mechanisms of consumer’s parasocial relationship with brands: utilitarian benefits, hedonic benefits, perceived self-disclosure, perceived interactivity, and perceived information overload. This study also investigates the effects of parasocial relationship on Facebook users’ online participation behaviors with brands and their offline brand loyalty. The hypothesized model is tested with multi-group SEM modelling. Practical and theoretical implications are also discussed in the study

Proposing the Affect-Trust Infusion Model (ATIM) to Explain and Predict the Influence of High- and Low-Affect Infusion on Web Vendor Trust

Trust is just as essential to online business as it is to offline transactions but can be more difficult to achieve-especially for newer websites with unknown web vendors. Research on web-based trust development explains that web vendor trust can be created by both cognitive and affective (e.g., emotion-based) influences. But under what circumstances will emotion or cognition be more dominate in trust establishment? Theory-based answers to these questions can help online web vendors design better websites that account for unleveraged factors that will increase trust in the web vendor. To this end, we use the Affect Infusion Model and trust transference to propose the Affect-Trust Infusion Model (ATIM) that explains and predicts how and when cognition, through perceived website performance (PwP), and positive emotion (PEmo) each influence web vendor trust. ATIM explains the underlying causal mechanisms that determine the degree of affect infusion and the subsequent processing strategy that a user adopts when interacting with a new website. Under high-affect infusion, PEmo acts as a mediator between PwP and vendor trust; under low-affect infusion, PwP primarily impacts trust and PEmo is dis-intermediated. We review two distinct, rigorously validated experiments that empirically support ATIM. To further extend the contributions of ATIM, we demonstrate how use of specific contextual features-rooted in theory and that drive one\u27s choice of affect infusion and cognitive processing-can be leveraged into a methodology that we propose to further enhance user-centered design (UCD). We further detail several exciting research opportunities that can leverage ATIM

Examining Users’ Information Disclosure and Audience Support Response Dynamics in Online Health Communities: An Empirical Study

Online healthcare communities (OHCs) facilitate two-way interaction. Examining users’ information disclosure-audience support response dynamics can reveal insights for fostering a supportive environment, community engagement, bond formation, knowledge sharing, and sustained participation in OHCs. We propose a structural vector autoregression (SVAR) model of user disclosure and response dynamics in OHCs. Based on the health disclosure decision-making model and daily time series data, we examine the two-way interaction of two dimensions of disclosure efficacy with audience support response acceptance. Findings of the impulse response functions reveal that user information density leads to positive support response acceptance, whereas support response acceptance reduces the information density of a user post over time. Further, higher information efficacy leads to more support response acceptance with long run improved information efficacy. Theoretically, findings extend the disclosure decision-making model in OHCs. Practically, the results provide insights for OHC management to facilitate two-way dynamic users’ interactions

Examining Users’ Information Disclosure and Audience Support Response Dynamics in Online Health Communities: An Empirical Study

Online healthcare communities (OHCs) facilitate two-way interaction. Examining users’ information disclosure-audience support response dynamics can reveal insights for fostering a supportive environment, community engagement, bond formation, knowledge sharing, and sustained participation in OHCs. We propose a structural vector autoregression (SVAR) model of user disclosure and response dynamics in OHCs. Based on the health disclosure decision-making model and daily time series data, we examine the two-way interaction of two dimensions of disclosure efficacy with audience support response acceptance. Findings of the impulse response functions reveal that user information density leads to positive support response acceptance, whereas support response acceptance reduces the information density of a user post over time. Further, higher information efficacy leads to more support response acceptance with long run improved information efficacy. Theoretically, findings extend the disclosure decision-making model in OHCs. Practically, the results provide insights for OHC management to facilitate two-way dynamic users’ interactions

Understanding the Platform Economy: Signals, Trust, and Social Interaction

Two-sided markets are gaining increasing importance. Examples include accommodation and car sharing, resale, shared mobility, crowd work, and many more. As these businesses rely on transactions among users, central aspects to virtually all platforms are the creation and maintenance of trust. While research has considered effects of trust-building on diverse platforms in isolation, the overall platform landscape has received much less attention. However, cross-platform comparison is important since platforms vary in their degree of social interaction, which, as we demonstrate in this paper, determines the adequacy and use of different trust mechanisms. Based on actual market data, we examine the mechanisms platforms employ and how frequent users rely on them. We contrast this view against survey data on users’ perceptions of the context-specific importance of these trust-building tools. Our findings provide robust evidence for our reasoning on the relation between platforms’ degree of social interaction and the associated expressive trust cues