To remain competitive in the realm of the Internet, developers of new business models not only have to take into account the behavior of online consumers, but also their misbehavior. Today, companies are faced with special challenges regarding consumer misbehavior, particularly in the segment of online content providers (e.g. Netflix, Amazon Prime Video, etc.), where it has become a common practice to share an account with multiple persons, while only one of them is the rightful owner. Such misbehavior may lead to negative consequences, such as direct and indirect financial performance implications, increased workload to deal with dysfunctional customer behavior, underestimated membership, and a lack of understanding the true customer base (Harris & Raynolds, 2003; Hwang et al., 2009). Therefore this study investigates account sharing as a part of customer misbehavior with a qualitative approach to identify customers’ reasons for account sharing. Thereby this investigation makes meaningful implications for companies (e.g., Netflix) and research alike.

Introduction Recent years have witnessed a rapid growth in peer to peer (P2P) sharing-service businesses such as Uber and Airbnb. In P2P sharing-service businesses, goods or services are provided by customers (peers) rather than by service firms, who act simply as an intermediary between customers. One customer acts as a service-providing customer (SPC), and the other as a service-receiving customer (SRC). P2P sharing-service firms have no direct control over an SPC’s quality of service provided to an SRC. Further, both SPCs and SRCs are customers to the firm, and therefore firms are concerned with the quality of service provided not only to SRCs but also to SPCs. In the P2P sharing-service context, particularly in the case of services serving the needs of diverse travelers (e.g., Uber or Airbnb), SPCs and SRCs can be people of different genders and races, which can cause them to feel socially distant from each other. Since SPCs are not professional service employees, they may not know how to cope with the social distance, which can result in uncomfortable service experience for both SPCs and SRCs. The more similar to the SPC an SRC feels, the more comfortable the SRC is likely to feel, which can lead to higher service satisfaction. Yet, few studies examined how such social distance can be reduced. This study is intended to fill this gap in the research. Specifically, we propose that an SPC’s form of address for SRC can moderate the effect of the incongruence in gender and race on an SRC’s perceived social distance. Theoretical Development Social distance refers to the level of acceptance people have of others outside of their own social group or class (Bogardus, 1928). It is a measure of perceived difference (or distance) between groups. In the context of the P2P sharing service, SRCs and SPCs can be from diverse social groups. When an SRC encounters an SPC from a social group that is different from theirs, the SRC can feel socially distant from the SPC. Immediate differences an SRC can identify upon meeting an SPC is demographic such as gender, age and race. In this study, we first propose that the difference (incongruence) in gender, age and race makes an SRC feel socially distant from an SPC. Social distance is closely related with similarity (Osbeck & Moghaddam, 1997; Liviatan, Trope & Liberman, 2009). In the context of mentoring, the higher the perceived and actual similarity a portage feels with a mentor, the higher the level of the portage liking and satisfaction for the mentor and with the mentoring service (Ensher, 1997). Matching gender and race between a mentor and a portage positively influenced self-reported grade point average, efficacy and confidence of a portage (Blake-Beard et al. 2011). Race was well demonstrated to influence social distance (Triandis & Triandis, 1960). Taken together, we conjecture that the effect of the difference in gender and race on social distance will apply to the P2P sharing service context and propose the following hypothesis: H1: The incongruence in gender and race between an SRC and an SPC will make SRCs feel more socially distant from SPCs compared to the case of congruence. We propose in this study that the form of address for SRCs by SPCs can influence the level of social distance SRCs feel because of the incongruence in gender and race. The relationship between forms of address and social distance has been proposed (Brown, 1965). Intimate terms of address is associated with intimate relationship. Intimate terms of address is inversely proportional to social distance (Keshavarz, 2001). Calling someone by the first name is related with friendliness (Brown, 1961). The use of first name is positively associated with closeness in relationship (Brown, 1965). An empirical study in the healthcare context showed that most patients preferred to be addressed by the first name (as opposed to last name) (Gillette, Filak & Thorne, 1984). Taken together, we propose the following: H2: Intimate forms of address by the SPC for the SRC will reduce the level of social distance caused by the incongruence in gender and race. We propose that the level of perceived social distance influences the level of comfort SRCs feel with the SPC during the service delivery. The negative effect of social distance on the level of interaction comfort has been shown (Paswan & Ganesh, 2005). In the context of service encounters where customers feel cultural differences, psychological distance was shown to influence comfort negatively (Weiermair, 2000). Since social distance is a dimension of psychological distance (Trope & Liberman, 2011), we propose the effect of social distance on comfort as following: H3: Reduced social distance will lead to a higher level of comfort. The effect of social distance on comfort can vary by customers. In this study, we propose that the effect is moderated by the customer’s motive for the purchase of the P2P sharing service. There are largely four movies for customers who participate in collective consumptions (i.e., sharing service): economic motive, social motive, hedonic motive, and the motive to reduce risks and responsibilities (Benoit, Baker, Bolton, Gruner & Kandampully, 2017). Economic motives are associated with reducing expenses, and social motives are with meeting other people (e.g. more authentic travel) (Benoit et al., 2017). Hedonic motives are related with “accessing products that are exciting or normally out of reach” while motives to reduce risks and responsibilities are related with “no burdens of ownership, option to preview a product for potential purchase” (Benoit et al., 2017). According to a research in the context of P2P accommodations, cost saving, familiarity, trust, and utility are determinants of satisfaction with a sharing option. Thus, we propose that customer motives moderate the effect of social distance on comfort (Möhlmann, 2015). H4: The effect of social distance on comfort vary by customer motives for purchase. When feeling comfortable, people are more likely to trust, feel satisfied, and commit themselves, which can help improve relationship (Spake, Beatty, Brockman & Crutchfield. 2003). Comfort positively influences perceived service quality and satisfaction (Dabholkar, Shepherd & Thorpe, 2000). Comfort influences satisfaction positively (Paswan & Ganesh, 2005). In the P2P sharing-service context, SRCs’ evaluation of SPCs are carried out by reviews. Customer reviews of SPCs’ services are vitally important for both SRCs and SPCs. Reviews help other SRCs to identify desirable SPCs (Ert, Fleischer & Magen, 2016) and SPCs to receive feedback for their service quality improvement. Therefore, we propose the following: H5: Comfort leads to SRC’s intention to write good reviews. Data Collection Data will be collected from American consumers who have used Uber at least once in the past one year through an online scenario-based survey using a 2 (genders: male vs. female) x 3 (races: white vs. yellow vs. black) x 3 (forms of address: no address vs. first name vs. last name) between-subject experimental design. Hypotheses will be tested by an analysis of variance and a structural equation modeling analysis. In the analyses, the potential effects of trust, familiarity, community belonging, utility (Möhlmann, 2015) and age will be controlled. Implications Findings of this study will reveal the importance of reducing social distance that SRCs feel during encounters with SPCs. Of many possible ways to reduce social distance between SRCs and SPCs, the result of this study will show that SPCs’ use of appropriate form of address to SRCs is effective. Further, it will show that the effect of social distance on customer comfort can vary by the purpose of the use of the sharing service. These findings will offer P2P service firms insights on how to help SPCs offer more comfortable services to SRCs and as a result receive positive reviews from SRCs.

Introduction The idiom “you are what you own” has been considerably transformed into “you are what you can access”. The shift from ownership to access, the results of endless hyper-consumption, and the change in value mindsets initiated a new phenomenon, which is Sharing Economy (SE). SE has grown rapidly and refers to an entirely new business model, socio-economic ecosystem, and context for sharing the access to goods and services in technology-enabled peer-to-peer (P2P) ecosystems or consumer-to-consumer (C2C) engagement platforms. According to Botsman and Rogers (2010), SE is a result of the linkage between offline and online world, which was triggered by the society to overcome natural resources constraints. Resources in SE can be tangible (e.g., cars and homes) and intangible (e.g., expert local knowledge and labor). SE allows the sustainable use of idle resources, and it enables sellers to create new and flexible opportunities to market to consumers who experience personalized and even customized products and services at lower prices (Yang, Song, Chen, & Xia, 2017). SE opened up new horizons for a considerable number of new players across industries from a supply perspective by broadening the options for supply, which also remedies the response to peak demand. SE has given a rise to the humanization of consumer-supplier relationship in tourism and hospitality (TH), and sharing has become a mainstream practice in this context. The recent shift of customers‟ willingness to share accommodation with a host as opposed to using a private hotel room has many implications for TH (Lu & Kandampully, 2016). For example, Airbnb has become one of the most prominent competitors in hotel industry, and it enables people to lease or rent short-term accommodation including vacation rentals, apartment rentals, homestays, and even experiences via instant booking. From cash-strapped travelers to high-end business travelers, Airbnb has revolutionized the TH service in a new form of contractual relationship and gained a well-grounded popularity. Some scholars, on the other hand, argued that SE is a “fundamentally different business model” which could make it a new marketplace instead of a direct competitor in hotel industry. From this point of view, Airbnb do not compete or pose a challenge to traditional TH services but extend the concept of TH (Lu & Kandampully, 2016). Hotel industry has reactively responded to the direct, indirect, and induced effects of Airbnb to economy, and Airbnb‟s impact on hotel industry have recently been researched by several scholars (Mody, Suess, & Lehto, 2017; Priporas, Stylos, Rahimi, & Vedanthachari, 2017; Zervas, Proserpio, & Byers, 2017). Customer engagement in TH has been empirically found to enhance customers‟ service brand evaluation, brand trust, and brand loyalty (So, King, Sparks, & Wang, 2016). Guests attach great importance to motivational drivers, more meaningful “beyond-purchase” social interactions and unique experiences in authentic settings, which give rise to customer engagement beyond the service encounter. Disruptive innovation theory also states that products or services that offer alternative benefits compared to conventional attributes can transform a market and attain a critical mass, which can be observed in Airbnb‟s story (Young, Corsun, & Xie, 2017). Airbnb is successfully promoting the mottos of “Belong Anywhere” and “Don’t Go There. Live There” to their guests. The feelings of trust and belonging were negatively changed by mass production and noncustom travel experiences, and people sometimes forgot the meaning of community due to high tendency of prestige and advertising. Consumers‟ changing attitudes towards utilization and accessibility compared to ownership created an indirect need for intimate connection between people, namely human connection. Then, social concerns upon products and services gave a rise to mass-customized product and service expectations of consumers. This is where Airbnb‟s value proposition comes into play. First, it creates not only financial but also personal rewards through a “personal concierge” and a “home away from home” experience. Second, Airbnb is not a simple transaction, rather it is deemed to be a lifetime experience. So “guest experience” is at the heart of Airbnb‟s strategic position. From the “experience” point of view, SE has also opened up new rooms for service research. Service in the context of Airbnb is considered as an experience, rather than a utilitarian relation. Also, service quality has always been a critical factor in highly-competitive service industries like TH. Service quality perception is multi-faceted, and the studies focusing on it are rather limited, especially in hotel industry. These studies highlighted the complexities associated with evaluating service quality and the contribution of service process delivery on service outcomes, which results in the perception of service quality. Therefore, perceived service quality can be influenced by different internal processes and interpersonal variables. In order to study service quality in Airbnb, the types of settings in this context are to be noted. There are two main types of hosting via Airbnb: (1) remote hospitality, which refers to hosting situations in which the host does not physically share the place with the guest (e.g. booking the entire place), and (2) on-site hospitality, where the host is physically present and sharing the apartment with the guest. Mainly, on-site hospitality is an important part of the sociability within the host–guest relationship. Priporas et al. (2017) studied service quality in the context of remote hospitality, and we decided to respond to their relevant call for future research on the other type of Airbnb accommodation, which is on-site hospitality referring to “Shared Rooms” and “Private Rooms” in Airbnb‟s listings. “Shared Rooms” refer to an exact communal experience with the host, and guests sleep in a space that is shared with others and share the entire space with other people. “Private Rooms” refer to privacy, to some extent, in which guests (i) value a local connection (ii) have their own private room for sleeping and (iii) may share some spaces with others. We do expect that human connection and experience gap can be better researched with on-site hospitality existing in “Shared Rooms” and “Private Rooms”. This is because hosts design their services to create and build a relationship with their guests, leading to superior guest experiences and the so-called positive moment-of-truth. In addition to the online storytelling on hosts‟ home pages, the most important moment-of-truth is created during the guests‟ stay at the host‟s place; thus, the host plays a major role in the customer‟s perception of service and the subsequent review of the experience (Lu & Kandampully, 2016). Considering the previously mentioned “experience gap” in the literature, our research question and relevant sub-questions are as follows: • What are the antecedents of perceived service quality in Airbnb on-site hospitality? o How well does SERVQUAL suffice for measuring perceived service quality in this context? o How well the cognitive and attitudinal factors expand this measurement? o What are the additional perceived service quality factors that can be derived from guests‟ online textual reviews to remedy the “experience gap”? Literature review Cheng (2016) conducted a systematic review of SE by using co-citation and content analysis of papers, and the findings reveal three distinct research areas of SE: (1) SE‟s business models and its impacts, (2) Nature of SE, and (3) SE‟s sustainability development. Moreover, two unique areas, specifically in TH, were identified: (1) SE‟s impacts on destinations and TH services and (2) SE‟s impacts on tourists. The comparison of both literatures has revealed limited expansion in TH literature despite the fact that TH are at the frontier of SE (Cheng, 2016). Pesonen and Tussyadiah (2017) conducted cluster analysis to identify user profiles corresponding to consumer motivations for using TH services of SE. They concluded that a consumer group uses TH services of SE to make their trips more convenient, while another group uses these services mostly for social reasons. Yang et al. (2017) studied the loyalty in SE services from relational benefits perspective and concluded that confidence and social benefits have significant and positive effects on commitment in SE services. Molz (2014) introduced the term „Network Hospitality‟, which is relatively new and rooted in old traditions of welcoming strangers. Airbnb represents just one of many types of network hospitality, and in Airbnb, trust is almost shaped based on peer reviews, not solely on one-to-one peer interactions. The online review information becomes the basis for members‟ reputation in the network. The information accumulated on Airbnb‟s online platform helps both parties to establish their reputation, as well as publicizing their personalities, thereby facilitating the process of finding the best match. Moreover, there are hundreds of people working in Airbnb‟s customer service, trust, and safety departments who are devoted to ensuring the intimacy provision of trusted services. Airbnb requires all hosts to abide by their “Hospitality Standards”, which include expected levels of cleanliness, commitment, and communication. The flexibility, reliability, and consistency of Airbnb‟s service providers help them to build and maintain the relationship Airbnb enjoys with their guests and hosts (Lu & Kandampully, 2016; Zervas et al., 2017). Pine and Gilmore (1998) predicted the rise of experience in their seminal study, referring to the “experience economy” and also stating “As goods and services become commoditized, the customer experiences that companies create will matter most.” They called this as “Staging Experiences”. Also, there exists evidence in literature that providers are shifting their focus from product- and service-oriented to design of quality experiences. In terms of the glamour of SE in TH, a “more unique experience” is deemed to be second only to better pricing. Airbnb may eventually address all elements of the accommodation experience, from travel reservations to ticketing for local attractions. Consumers are looking for local authenticity in their travels. Psychological authenticity refers to emotional genuineness, self-attunement, and psychological depth (Walls, Okumus, Wang, & Kwun, 2011). If TH industry is to surpass its SE competition in terms of guest experience, it should leverage an expanded experience economy paradigm that incorporates additional dimensions (Mody et al., 2017). Authentic host-guest experiences probably only exist between like-minded and privileged members who possess high cultural capital (Cheng, 2016). With that, Walls et al. (2011) have suggested the need for researchers to identify specific dimensions “that exist in both our everyday and tourist experiences”. Both in Airbnb and traditional TH, guest satisfaction and likelihood to reuse are driven by similar factors such as quality and utility of services, trust to the host, and economic value. There are several models for measuring service quality, including SERVQUAL (Parasuraman, Zeithaml, & Berry, 1988) and SERVPERF (Cronin & Taylor, 1992). Service quality literature received widespread attention after the seminal work by Parasuraman et al. (1988) as they proposed the gap model and developed SERVQUAL (an attribute-based technique) as a tool for measuring service quality. According to SERVQUAL, service quality consists of five dimensions measured by a total of 22 items. The proposed five service quality dimensions are tangibles, reliability, responsiveness, assurance, and empathy. SERVQUAL basically requires measures of expectations and performance, and service quality is calculated from subtractions between these two components (i.e., performance [P] - expectations [E]). Regarding service quality in TH, Akbaba (2006) utilized SERVQUAL for business hotels, and Priporas et al. (2017) inquired SERVQUAL‟s applicability in Airbnb context with promising results. The major distinction between two research directions (i.e. hotels vs. Airbnb) is that even though guests expect similar core services such as clean rooms and comfortable beds, different attributes support the competitive advantage of hotels and Airbnb. While conveniences offered by hotels are unparalleled by Airbnb accommodation, the latter appeal to consumers driven by experiential and social motivations (Pesonen & Tussyadiah, 2017). Research model This research aims to identify the antecedents of perceived service quality of guests‟ in Airbnb on-site hospitality context. Our research model is presented in Figure 1, and it is subject to enhancement through the analytics of guest reviews. A survey will be developed to test the proposed research model. The items of constructs will be mainly derived from extant literature and enriched with the linguistic and textual analysis of reviews. Firstly, factors shaping expectation are predicted as per the literature and preliminary analysis of random guest reviews: (i) host‟s reputation capital (e.g., ratings and reviews), (ii) host‟s photos, (iii) guest‟s past accommodation experience, and (iv) word of mouth. Secondly, SERVQUAL part in the model is the same as proposed by Parasuraman et al. (1988). Last but not least, Airbnb is deemed to promote global geographical imaginaries (e.g., collaboration, social equity, solidarity, community, trust, reciprocity, altruism, autonomy, intimacy, and authenticity) to justify their business model (O‟Regan & Choe, 2017). Finally, regarding the guest review analysis, Airbnb has a detailed review mechanism, and we have gathered the publicly available reviews that are up to 500 words. We have observed cognitive and attitudinal dimensions within reviews through text analytics and grouped those in the research model as follows: • Intimacy: The emergence of intimacy as a commercial value in TH industry has been researched. (e.g., How well people know each other? How people occupy space together? How people share private information, family pictures, furniture choice etc.?) (Prager, 1997) • Authenticity: We focus on the existential authenticity (i.e., being one‟s true self or being true to one‟s essential nature) from guests‟ perceptions (e.g., Is Airbnb like ‘living the local life’?) (Lalicic & Weismayer, 2017) • Commitment: It refers to the consistent behavior of Airbnb hosts in terms of social and cost components. (e.g., How well hosts abide by Airbnb policies and procedures? Do hosts have ongoing effectiveness of service?) (Lu & Kandampully, 2016) • Privacy: It refers to the psychological zone to disclose personal and cultural values. Informational and physical privacy threats are important in Airbnb context (Lutz, Hoffmann, Bucher, & Fieseler, 2017). • Security: It refers to the state of being free from danger or threat. According to Yang and Ahn (2016), security in Airbnb‟s services is a more powerful antecedent of attitude toward Airbnb than significant dimensions of motivation toward SE, such as enjoyment and reputation. With that we will only elaborate on interpersonal security in Airbnb (i.e., between host and guest, not between guest and Airbnb). Conclusion SE is a fairly new and multi-disciplined field that covers open rooms for research, and specifically, Airbnb is one of the most prominent businesses in this context. The literature review presented underlies the infancy of well-grounded studies covering service quality perceptions of customers in SE. Seeking for additional dimensions from Airbnb guests‟ reviews is a novel research approach in studying customer engagement, and those dimensions shall be included in the research model. This research has certain limitations. Our perceived service quality conceptualization requires empirical validation to establish the boundaries of the construct. The guest reviews in Airbnb are subject to data quality issues. Also, reviews should contain substantial amount of words up to a certain threshold. Data collection from emerging world regions is rather tough since Airbnb is not widespread across those regions. Thus, US and European countries will be firstly taken into account, where the use of Airbnb is quite common. The study is expected to provide useful insights for TH practitioners and managers. It can underlie the factors that trigger customer engagement in this context. Cognitive/attitudinal factors are foreseen as the differentiators, which stand as the basis for service design and delivery.

Introduction In order to solve the information asymmetry and make full use of resources (unused goods, spare capacity and so on), the sharing economy, which based on the application of mobile internet technology and focused on the consumption of the right to use, is developing rapidly. Lack of trust is considered to be one of the important problems hindering the development of sharing economy. Möhlmann (2015) said that trust is a fundamental determinant of sharing economy development and ensuring shared satisfaction. At present, sharing economy enterprises have established product evaluation system and docked a third party credit rating system (i.e. Zhima Credit) to promote consumers’ trust. However, with most enterprises are becoming more and more consistent in evaluation and credit rating system, there is a new problem emerged: how to further deepen consumers’ trust in order to promote consumers’ intention to participate continuously (Zucker, 1986; Lewis & Weigert, 1985). Granovetter (1985) mentioned that trust is the product of social relationships. Botsman and Rogers (2011) made it clear that social networks play an important role in building trust in sharing economy. And people are always more willing to accept the opinions of people who have social relations with them (Lu, Zhao, & Wang, 2010). Hence, with the feature of participant of everyone in sharing economy, it is necessary to further strengthen consumers’ trust through the social interaction among consumers and between consumers and sharing platforms. Theoretical Development Sharing economy is based on LBS and other new technologies to realize the matching of supply and demand information across time and space. And to a certain extent, it solves the problem of information asymmetry in the era of e-commerce. Yet consumer have new requirements for product information. For example, consumers are more concerned about whether the utility of products and services can meet their needs (i.e. some consumers are more concerned about when to reach their destination than the performance of the car). But it is difficult for company to understand each everyone of consumers’ utility preference and publish product utility information based on these preferences (Xie & Gerstner, 2007). Because this kind of utility preference has the characteristic of timeliness and personalization. Therefore, consumers’ perceived uncertainty about the utility of the product will also affect the consumers’ trust. In summary, we then address these research questions:(1) can the promotion of trust between consumers and sharing platforms be achieved through the socializing of sharing platforms and then affect consumers’ intention to participate continuously; (2) if so, which type of privacy protection method and social information can promote consumer trust; and (3) does the impact of sharing platform socialization on consumer trust vary according to consumers’ concerns about the perceived utility uncertainty of the product. Research Design We then address these issues using experiment data. The first experiment was a 2 (social media: have, not have) x 2 (individual trust propensity: trust, not trust) between-subject design on the intention to trust sharing platform and participant continuously. Perceived utility uncertainty was added to this design as a moderator. Moreover, the second experiment was a 2 (social information type: hedonic, utilitarian) x 2 (degree of privacy protection: week, strong) between-subject design on the intention to trust sharing platform. Our scales come from existing scales and optimize it according to the characteristics of sharing economy (Schneider, 1999; Dhar & Wertenbroch, 2000; McKnight, Choudhury, & Kacmar, 2002). Results and Conclusion The results of the first experiment show that whether or not the social platform has no significant impact on the consumer trust if the individual tends to trust others. And for individuals who tends to do not trust others, they are more likely to trust socialized sharing platforms. The higher the consumer perceived utility uncertainty is, the higher (lower) trust of the consumer platform in the socialized (not socialized) sharing platform. For the second experiment results, in the context of sharing economy, the utilitarian information has a greater positive impact on the consumer trust than the hedonic information. In addition, the stronger the privacy protection of sharing platforms, the higher the trust of consumes. This study makes several academic contributions. First, we extend the topic of socialization to sharing economy context. Second, we add the perceived utility uncertainty as a moderator, and supplement the role of perceived uncertainty. This research also provides several practical implications. First, sharing platform can promote their consumers’ trust by establishing their own social platform. This platform can be used as a differentiated competitive strategy for sharing platform. Second, sharing platform should guide consumers to share utilitarian information (i.e. weather for specific place or real time traffic) to improve consumer satisfaction. Third, sharing platform can access consumer preference information through this social platform for further product development and classification.

Due to the explosive growth of peer-to-peer transportation sharing services offered by micro-entrepreneurial travelers, investigating how their quality cues affect demand is of paramount importance. The goal of this study was to identify what types of intrinsic and extrinsic quality cues affect the demand of peer-to-peer transportation sharing services. Based on the rich data set of 414,292 transactions from a leading peer-to-peer ridesharing platform, it was identified that intrinsic quality cues – car status and driver status – and extrinsic quality cues – price and offering duration – significantly affect the peer-to-peer transportation demand independently and interactively. Although the lower price and longer offering duration of a transportation sharing service positively affect its demand, the higher price or shorter offering duration can increase its sales when combined with better intrinsic cues. Implications for vulnerable segments such as female and minority drivers are provided

Previous research has found that taking photos during travel for the purpose of sharing with others via SNS (social networking sites) induces self-presentational concerns, which can decrease engagement and enjoyment of the experience. However, the previous studies have defined travel engagement and enjoyment too narrowly and failed to consider the heterogeneity in terms of the importance of photo-taking. While some travelers are reluctant photo takers and regard taking photos as a bother, others place more importance on photo-taking than sightseeing, and may therefore find it difficult to enjoy the travel experience without taking photos. To address these deficiencies, we modeled not only negative, but also positive relationships between photo-taking and travel engagement and enjoyment. The results showed that when taking photos, travelers who regard photo-taking as important were more engaged in the experience and enjoyed it more than travelers who regarded photo-taking as less important. Thus, this study provides a theoretical contribution to research on travel engagement.

For better understanding user behavior, especially exploring what factors would motivate user engagement in sharing economy and whether there are some differences between people behaviors in sharing economy and conventional economy, this research developed a conceptual framework of user engagement (UE) in sharing economy on the basis of customer engagement and related literature and tested it through empirical analysis.

Marketing in the sharing economy The shift on the enhanced complexity of customers‟ needs has created a new business model termed as the sharing economy emerging through the traditional B2B2C sector, and substituted with micro-entrepreneurs who act as service providers (Kumar, Lahiri, and Dogan, n.d.). The importance of the sharing economy is based on the fact that in a short period of time it has managed to disrupt well-established fields (i.e.: taxi and accommodation industry), through the provision of low-cost convenience without the ownership responsibility (Eckhardt & Bardhi, 2015). In general, the sharing economy service providers are not responsible for marketing and promotional aspects since this is an aspect taken care of the service enablers (i.e.: Airbnb). In the sharing economy, marketing needs to focus on the development of early adopters, meaning younger generations (Laciana & Rovere, 2011), since they are the largest generational cohort, and are expected to remain the largest one for the forthcoming decades (Fry, 2016), whilst they have a considerably lower spending capacity than older people (Henderson, 2016). Therefore, younger generations select cost-efficient options and engage in utility-based brand switching (Kumar et al., n.d.). As a result, sharing economy marketing strategies mainly focus on apps or websites where their existing customers may visit (McAlone, 2016). Moreover, multigenerational marketing is considered as a rational segmentation strategy for service enablers (Eckhardt & Bardhi, 2015), since the older a generation is the lower the general adoption rates in sharing economy marketing (Hall & Krueger, 2015). Still, the complex decision-making of consumers in sharing economy‟s marketing is affected by several factors such as price and quality issues and the associated risks (Pappas, 2017). Despite the importance of sharing economy in modern business, the literature is silent on the complexity of aspects affecting the related marketing activities. The paper examines the complexity of marketing activities formulation examining peer-to-peer (P2P) accommodation holidaymakers in Athens, Greece. It specifically evaluates the impact of risks, price and quality issues, and social aspects, on P2P accommodation marketing activities, also including the socio-demographics of age and income. The research contribution is in both, theoretical and methodological domains. In terms of literature the study provides an understanding of the complexity formulation of marketing activities, with special reference to the sharing economy. Methodologically-wise, the research implements fuzzy-set Qualitative Comparative Analysis (fsQCA), which is considered new to the study of tourism and hospitality (Pappas & Papatheodorou, 2017). It further compares fsQCA suitability with regression, which is the dominant correlational mode of analysis. Study tenets In service industry research the term „tenet‟ is used to describe testable precepts able to identify complex conditions (Papatheodorou & Pappas, 2017). This study has formulated six tenets: (T1) The same attribute has the ability to determine a different decision for marketing activities depending on its configuration with other attributes (T2) A complex configuration with at least two simple conditions can leads to an outcome condition that can have a consistently high score (Recipe principle) (T3) Complex configurations can influence the marketing activities for P2P holidaymakers (T4) When the combinations differ on the simple conditions of configurations, they can influence in a positive or negative manner the marketing activities for P2P holidaymakers (T5) Sufficient marketing activities do not always result in a high outcome score (Equifinality principle), and (T6) When the Y scores are high, a given recipe for the marketing activities is not relevant for all cases. Complexity in tourism Complexity theory focuses on complex systems with nonlinear dynamics, characterised by self-organisation, emergence, and evolution (Arévalo & Espinosa, 2015). The theory is used to evaluate the nonparametric, and dynamic processes of complex phenomena in several different disciplines (Olya & Al-ansi, 2018). Tourism complexity is based on several conflicting elements, such as the translocal relationships and multilocality, the heterogeneity of actors, the places and governance globalisation, and the extreme diversity of operations (Darbellay & Stock, 2012). Moreover, tourism deals with complex policies involving multiple actors, and a perpetually changing multi-level coordination in a local, national and international level (Lai, Hsu, and Wearing 2016). The degree of behavioural complexity renders Newtonian (linear) thinking inadequate and highlights the necessity for nonparametric (nonlinear) research (Laws & Prideaux, 2005). Method The study was held in Athens, Greece in adult P2P accommodation holidaymakers. Following the study of Pappas (2017), structured questionnaires were distributed to the P2P rentals, asking from the holidaymakers to fill them in during their stay. As Akis, Peristianis and Warner (1996) suggest, the study‟s sample size should have a minimum of 95 percent level of confidence and a maximum of 5 percent statistical error, whilst the most conservative response of 50/50 (meaning half of the respondents would express positive views and the other half negative ones) was adopted. For N>20, t-table defines cumulative probability (Z) in 1.96 level. Following Akis et al. (1996), the sample size calculation is: Rounded to 400 In total, 712 useful responses were collected, generating a statistical error of 3.67 per cent. The questionnaire consists of 24 Likert scale statements adopted from previous research, including two socio-demographic questions (age; income). The study employed fsQCA for the evaluation of complex configurations. fsQCA is considered a mixed method since it employs quantitative testing and qualitative inductive reasoning, and it is able to examine the potential complex relationships that have a bearing upon the outcome of interest, and identifies combinations of binary sets generated from its predictors. Since the research also estimated negated sets (presence or absence of a simple condition), the symbol “~” was used for the indication of an attributional absence. Research calibration was made by using 42 randomly selected individual cases. For the evaluation of the marketing activities „f_ma‟ affecting holidaymakers, the calibrated fuzzy-sets used were „f_a‟ for age, „f_i‟ for income, „f_r‟ for risks, „f_sa‟ for social aspects, „f_pi‟ for price issues, and „f_qi‟ for quality issues. Results Three sufficient configurations emerged from the research. More specifically, the first solution (f_a*f_i*~f_r*~f_sa*f_pi*f_qi) concerns the price-quality nexus, the second configuration (f_a*~f_i*f_r*~f_sa*f_pi*~f_qi) deals with price sensitivity, and the third one (f_a*~f_i*f_r*f_sa*~f_pi*f_qi) focuses on social interaction. The generated solutions for marketing activities are presented in the table below. The results indicate that all four simple conditions appear in at least one solution (T1), whilst at least two simple conditions are included in each sufficient configuration (T2). Moreover, the findings suggest that the solutions focus on: (i) price-quality nexus (ii) price sensitivity, and (iii) social interaction (T3). In addition, none of the simple conditions appears in all configurations (T4), and three different solutions seem to lead to the same outcome (T5). Finally, the coverage varies from .429 to .453, meaning that none of the solutions applies in all cases (T6). As a result, the findings confirm the six tenets of the study. fsQCA versus regression The study used a structural equation model for the examination of linear relationships, and implemented Confirmatory Factor Analysis (CFA), since the sum of the examined items is based on previous analytic research. Due to the large sample (N=712) χ2/df instead of χ2 was selected, since it is considered as a better estimate of goodness (Chen & Chai, 2007). Following Kline (2010), the research estimated the four most important fit indices: χ2=634.921, df=352, χ2/df=1.803 (acceptable value 0≤χ2/df≤2 [Schermelleh-Engel, Moosbrugger & Müller, 2003]), CFI=.902 (acceptable value is when CFI is close to 1.0 [Weston and Gore 2006]), SRMR=.782 (acceptable value is when SRMR<.8 [Hu & Bentler, 1999]), and RMSEA=.475 (acceptable value is when RMSEA<.5 [Browne & Cudeck, 1993]). In factor analysis, all values less than .4 were suppressed (minimum acceptable value .4 [Norman & Streiner, 2008]) in an effort to evaluate higher coefficients. In all constructs, the Average Variance Explained (AVE) was higher than .5 (minimum acceptable .5 [Kim, 2014]), and the convergent validity (CR) higher than .7 (minimum acceptable value: .7 [Huang, Wang, Wu, & Wang, 2013]). The Figure below explains the study‟s endogenous variables. The comparison of fsQCA with regression highlights that the latter cannot encapsulate the full range of alternative combinations, in restricts the presence/absence of a construct or socio-demographic in one outcome, whilst the row coverage in all sufficient configurations (also showcasing high consistency) is higher than the overall R2 (.393). As a result, fsQCA seems to be more efficient than regression concerning the examination of marketing activities on P2P holidaymakers, since it better presents the influence of the constructs under examination. Managerial implications The study offers a number of managerial implications. For starters, through the use of fsQCA, traditional accommodation providers and destinations can better understand complexity aspects of consumer trends, being able to sufficiently reposition their marketing activities. Moreover, fsQCA can assist on the clarification of the factors affecting marketing complexity in tourism and hospitality, and better promote and advertise the products and services in reference. The understanding of complex marketing patterns, can further lead to the formulation of competitive advantages and strengthen the competitiveness of the enterprises engaged in a destination, as well as the destination itself. In addition, destinations can better comprehend the complex evolution of sharing economy and build upon its strengths, aving the opportunity to formulate a cooperative market towards traditional establishments and P2P rentals. Limitations Despite the theoretical and methodological contribution of the study, several limitations need to be highlighted. The main limitation derives from the study‟s main strength, which is the limited application of fsQCA in tourism and hospitality. Much further use of fsQCA in the field could reveal its full potential. Another limitation deals with the examination of other groups, such as the holidaymakers selecting traditional establishments for their stay, P2P stakeholders, and destination authorities. Since different groups of respondents may produce different outcomes, any generalisation of the findings should be made with caution. Finally, if the research is repeated in some other destination or in later time, the focus of the generated complex configurations may alter. Therefore, the results should be carefully interpreted.

Using the framework of social support, we aim to examine factors influencing social Word-of-Mouth (WOM) adoption. The proposed research model will be tested among customers who are active in the existing active social media platforms and have had experience in engaging with the activities of luxury brand communications. Introduction Today the most promising communication environment for reaching and interacting with stakeholders is the social media ecosystem (Hanna, Rohm and Crittenden, 2011). The social media has grown so rapidly in the past years that now impact the business processes and models (Henning-Thurau, Hofacker and Bloching, 2103). Many Brands begin to take advantage of the fluidity between social media and WOM for creating brand experiences that merge real and digital conversations, cutting through in incredibly powerful ways. However, the recent research (Godey, Manthiou, Pederzopli, Rokka, Aiello, Donvito and Sigh, 2016) suggest that luxury brands performing well in social media engagement. However, they are often lagged behind in WOM performance. Despite growing interest in examining the influence of social media marketing on consumer’s responses through brand equity creation (Godey et al., 2016; Jim and Ko, 2012), studies about social media in luxury brand communications remain to be scarce. An investigation of customer’s motivation behind participation in social media is timely and relevant which can help luxury brands unleash its potential. Moreover, development of an effective social WOM adoption model can help to provide a better picture of consumer interactions in online luxury brands communities, thus strengthen customerfirm relationship in longer term. Specifically, this research intends to answer the following two questions: 1) What are the major determinants of social WOM adoption in luxury brands communications? 2) Whether social support affects a. perceived source credibility; b. perceived information quality; c. user experience? Literature review Social media interactivity The concepts of social exchange (Blau, 1964) and the norm of reciprocity (Gouldner, 1960) have long been used by Marketing researchers to describe the motivational basis behind customer behaviours and the formation of positive relational attitudes (e.g., Wulf; Gaby; Iacobucci, Dawn, 2001; Rafiq; Fulford and Lu 2013). More recently these concepts have been used to explain why customers enjoy interacting with each other in social media (Liang, Ho, Li and Turban 2012; Godey et al., 2016). Social media interactivity is social interaction of people in social networking sites by Web 2.0 technologies such as Facebook, Instagram (Hajli, 2016). For instance, Facebook has more than two billion monthly active users which is a great example of a platform. In fact, people love to interact with each other. When they favourite and like each other’s posts that would reinforce the closeness. Online social support Recent research has found that social interaction can bring social value to their users and that the social media is a powerful vehicle for an individual to build close relationships with others and to enhance the individual’s well-being (Liang et al., 2012; Eastin and LaRose, 2005; Obst and Stafurik, 2010; Shaw and Grant, 2002; Xie, 2008). Social support has been found to be a major social value that social media users can obtain from an online interactions (Eastin and LaRose, 2005; Obst and Stafurik, 2010; Huang, Nambisan and Uzuner, 2010). Social support is a multidimensional construct which refers to an individual’s experience of being cared for, being responded to, and being helped by people in that individuals’ social network (Cobb, 1976). Schaefer, Liang et al.(2012) claim that , online social support consists both tangible (e.g. instrumental and appraisal support) and intangible elements (e.g. informational and emotional support). Given the specific context, this study mainly focuses on the latter. Informational support refers to providing messages, in the form of recommendations, advice, or knowledge that could be helpful for solving problems. By contrast, emotional support refers to providing messages that involve emotional concerns such as caring, understanding or empathy. These two types of messages are the major support mechanisms for social interactions (Hajli, 2016). Antecedents of social WOM adoption Information adoption can be defined as the process of engaging purposefully in consuming information (Cheng and Thadani, 2012). Informational support provided through social interaction of individuals in social media can be in the form of ratings, review, recommendations or referrals. Therefore, when consumers search for information provided by other users to make a better decision for their purchasing, they are adopting information. From a marketer’s perspective, this process also helps to build long-term advocacy. This research argues that social media provides more opportunities to the individual to adopt WOM. The existing literature has identified several antecedents of social WOM adoption and most of these studies focused on travelling websites (Filieri; Alguezaui and McLeay,2015; Hajli, 2016). Beldad, De Jong, Steehouder (2010) have categorized the major antecedents of social WOM adoption in the literature into three categories namely customer-based antecedents (e.g. user’s experience during the social interactions); website based antecedents (e.g. perceived information quality) and company based antecedents(e.g. perceived source of credibility). Source of credibility is considered as fundamental predictors of consumers’ acceptance of a message in traditional WOM adoption (McGinnies and Ward, 1980). To facilitate the evaluation of credibility of a source, more and more social platforms require contributors to create a web profile upon their registration. Customers need to provide personal information (e.g. profile picture, personal preference). Furthermore, many social media website utilise reviewer reputation systems to enable customers to assess the credibility of reviewers. Zhang and Watt (2008) argue that the higher source credibility of message perceived in online social media, the higher level of information adoption would be. Moreover, the quality of information in online reviews is perceived as a very important cue for consumers to assess the website (Filierri, et al., 2015). Krishnan; Biswas and Netemeyer (2006) point out that concrete information provided by the website such as detailed features of the product/service is likely to be perceived as more credible than those from abstract information like peripheral description of the product/service. Finally, in marketing literature user experience is strongly related with trust (Yoon, 2002). In an online context customers’ negative experience is likely to affect their trust about the company. As a consequence, they are likely to engage in negative WOM. Research shows that user experience has a strong impact on the social WOM adoption (Liang et al., 2012). Method Structural Equation Modeling (SEM) will be employed for examining the research objectives of this research. The questionnaire for this study will be created through a professional online-based survey tool. As this research focuses on the factors influencing social WOM adoption in relation with luxury brands communications, the proposed research model will be tested among customers who is active in the existing active social media platforms and has had experience in engaging with the activities of luxury brand communications such as posting review or comment other’s post). Result and conclusion This research has adopted the electronic WOM theory and the social media support theory along with a social media perspective to investigate how customer’s interaction in social media affects their behaviour in relation to luxury brands consumption. The results show that social WOM facilitates the evaluation by customers about the luxury products using social media. Moreover, WOM has emerged with broad accessibility and the capability to be evaluated and measured easily by other consumers. This study gives practical implications on how to use social media to develop online communities for luxury brands. In conclusion, when going online, luxury brand should consider the importance of converting the online brand strategy into an interactive and engaging experience for their users and online communities.

This study empirically examines the effects of two distinct types of privacy-related concerns (organizational threats and social threats) on different aspects of information disclosure (amount, honesty and conscious control) on social network sites, especially by highlighting the role of trusting beliefs (integrity & honesty, predictability, benevolence, competence), across three markets in which social network usage is substantial (i.e. US, Europe, and East Asia). The study contributes to the literature focused on the paradoxical dichotomy between privacy attitudes and behaviors. In a quantitative modeling framework, we develop a structural model based on our previous conceptual model. We use data collected through snowball convenience sampling technique from a large sample (n=624), Web-based consumer survey from Europe, US and East Asia to measure these constructs, and we fit a series of structural equation models that test related prior theory. Findings suggest that the “Social Sharing” paradox may result from a failure to disentangle between social and organizational concerns, since the authors find no effect of privacy concerns about organizational threats on overall disclosure (amount and honesty of information) but find high conscious control of information disclosed for higher concerns towards social threats. Trusting beliefs differently influence information disclosure in the three main geographical areas and were found to moderate the effect of social concerns on the amount of information disclosed and conscious control. Further the cross-country analysis results suggest that cultural values may affect how concerns about privacy and trusting beliefs, impact self-disclosure. For practice, our research suggests actionable strategies to aid online marketers in matching information requests with the needs and concerns of consumers by providing greater control and customization and enhancing firm trust.

The dual processes of cognition and affect impact consumers’ choice of sharing economy-based experiential tourism. Prior knowledge of sharing economy technologies and favourable attitude toward sharing economy impact consumers’ intention to adopt a peer-to-peer experiential tourist service. Data from 150 respondents and OLS and OLogit analyses supported the hypothesis.

Ever since the notion of a sharing economy was highlighted by Time Magazine as one of the ten ideas that will one day change the world, there has been a significant increase in scholarly attention dedicated to investigating the impact sharing economies will have on individuals, organizations and society as a whole. Particularly, sharing economy has revolutionized the landscape of the tourism industry through Airbnb (Fang, Ye, & Law, 2016). Academic research has focused on studying consumption practices and behaviors from a recipient perspective, but relatively little attention has been given to understand what impacts sharing economy has, from a sharer point of view (Fagerstrøm, Pawar, Sigurdsson, Foxall, & Yani-de-Soriano, 2017). Specifically, the existing literature has yet to explore in what ways and to what extent sharers are engaged with sharing economy platforms, and explore what consequences accrue from engaging in sharing economy activities. As a result, this paper seeks to fill this gap by proposing a framework drawing on self-determination theory (SDT), in conjunction with a tourism well-being perspective to examine how sharers’ perception of extrinsic rewards indirectly influences their well-being through the mediating role of engagement in tourism sharing economy activities. Data from Airbnb hosts in London were analyzed through PLS. The findings show that hosts’ engagement with Airbnb fully mediates the relationship between extrinsic rewards and their wellbeing. In other words, extrinsic rewards from using the sharing platform have a positive effect on sharers’ engagement in sharing economy activities (Tussyadiah & Pesonen, 2016; Guttentag, 2015). In turn, engagement in sharing economy activities has been found to have a positive effect on the sharers’ well-being (Kim, Uysal, & Sirgy, 2013; Ganju, Pavlou, & Banker, 2016). The paper has some important managerial implications.

Introduction In order to solve the information asymmetry and make full use of resources (unused goods, spare capacity and so on), the sharing economy, which based on the application of mobile internet technology and focused on the consumption of the right to use, is developing rapidly. Lack of trust is considered to be one of the important problems hindering the development of sharing economy. Möhlmann (2015) said that trust is a fundamental determinant of sharing economy development and ensuring shared satisfaction. At present, sharing economy enterprises have established product evaluation system and docked a third party credit rating system (i.e. Zhima Credit) to promote consumers’ trust. However, with most enterprises are becoming more and more consistent in evaluation and credit rating system, there is a new problem emerged: how to further deepen consumers’ trust in order to promote consumers’ intention to participate continuously (Zucker, 1986; Lewis & Weigert, 1985). Granovetter (1985) mentioned that trust is the product of social relationships. Botsman and Rogers (2011) made it clear that social networks play an important role in building trust in sharing economy. And people are always more willing to accept the opinions of people who have social relations with them (Lu, Zhao, & Wang, 2010). Hence, with the feature of participant of everyone in sharing economy, it is necessary to further strengthen consumers’ trust through the social interaction among consumers and between consumers and sharing platforms. Theoretical Development Sharing economy is based on LBS and other new technologies to realize the matching of supply and demand information across time and space. And to a certain extent, it solves the problem of information asymmetry in the era of e-commerce. Yet consumer have new requirements for product information. For example, consumers are more concerned about whether the utility of products and services can meet their needs (i.e. some consumers are more concerned about when to reach their destination than the performance of the car). But it is difficult for company to understand each everyone of consumers’ utility preference and publish product utility information based on these preferences (Xie & Gerstner, 2007). Because this kind of utility preference has the characteristic of timeliness and personalization. Therefore, consumers’ perceived uncertainty about the utility of the product will also affect the consumers’ trust. In summary, we then address these research questions:(1) can the promotion of trust between consumers and sharing platforms be achieved through the socializing of sharing platforms and then affect consumers’ intention to participate continuously; (2) if so, which type of privacy protection method and social information can promote consumer trust; and (3) does the impact of sharing platform socialization on consumer trust vary according to consumers’ concerns about the perceived utility uncertainty of the product. Research Design We then address these issues using experiment data. The first experiment was a 2 (social media: have, not have) x 2 (individual trust propensity: trust, not trust) between-subject design on the intention to trust sharing platform and participant continuously. Perceived utility uncertainty was added to this design as a moderator. Moreover, the second experiment was a 2 (social information type: hedonic, utilitarian) x 2 (degree of privacy protection: week, strong) between-subject design on the intention to trust sharing platform. Our scales come from existing scales and optimize it according to the characteristics of sharing economy (Schneider, 1999; Dhar & Wertenbroch, 2000; McKnight, Choudhury, & Kacmar, 2002). Results and Conclusion The results of the first experiment show that whether or not the social platform has no significant impact on the consumer trust if the individual tends to trust others. And for individuals who tends to do not trust others, they are more likely to trust socialized sharing platforms. The higher the consumer perceived utility uncertainty is, the higher (lower) trust of the consumer platform in the socialized (not socialized) sharing platform. For the second experiment results, in the context of sharing economy, the utilitarian information has a greater positive impact on the consumer trust than the hedonic information. In addition, the stronger the privacy protection of sharing platforms, the higher the trust of consumes. This study makes several academic contributions. First, we extend the topic of socialization to sharing economy context. Second, we add the perceived utility uncertainty as a moderator, and supplement the role of perceived uncertainty. This research also provides several practical implications. First, sharing platform can promote their consumers’ trust by establishing their own social platform. This platform can be used as a differentiated competitive strategy for sharing platform. Second, sharing platform should guide consumers to share utilitarian information (i.e. weather for specific place or real time traffic) to improve consumer satisfaction. Third, sharing platform can access consumer preference information through this social platform for further product development and classification.

Car-sharing is one of the most popular cases of a shared economy. It is a sustainable service that enhances mobility by renting shared vehicles to meet user's purpose in short-time. Car-sharing has known that it is effective in reducing ownership of passenger cars, reducing traffic congestion, and improving the environment. In Korea, a variety of car-sharing services have been launched, and since 2012, Korea Land & Housing Corporation (LH) has started to introduce HappyCar service for residents of public rental housing complexes nationwide. Public rental housing complexes have three types of complexes, one of which is complex for the low-income households. The purpose of this study is to find out the factors affecting the use of carsharing for low-income people using Poisson regression analysis with 2017 HappyCar usage data. Data including outliers was filtered and explanatory variables (age, sex, and accessibility of public transportation around rental housing complexes) were selected through correlation analysis. The results of this study are expected to be useful for analysis of carsharing low-income users' behavior, demand forecasting, and the establishment of shared transportation policies in the future.

The government focuses the innovation paradigm of public institutions on the realization of social value through national tasks. Efforts are now being made to legislate the Framework Act on the Realization of Public Institutions’ Social Value, which allows public institutions to serve as the foundation and check the progress of social value realization plans every year. According to this Act, the government performance review must also reflect efforts and outcomes made to create social value. Traditional public institutions in the road sector are trying to convert social responsibility, job creation and related activities into indicators of social value realization. Social value refers to a “value that can contribute to public interests and community development in all areas including social, economic, environmental, and cultural ones.” This definition commonly used in government policy includes the concept of public institutions’ social responsibility and shared value creation. Here, social responsibility refers to the returning of corporate profits to society for the continued development of a community while shared value creation refers to the solving of a social problem by a company pursuing both economic and social value creation. The performance sharing scheme in particular is regarded as an important tool for companies to create social value. In this regard, this study examines how public institutions in the road sector used the performance sharing scheme. The purpose of this study is also to discover more cases based on this analysis. The analysis so far found the following 5 types of performance sharing schemes in the road sector: (a) service improvement, (b) technology development, (c) conditional purchasing, (d) technology transfer, and (e) performance sharing between multiple parties. Notably, technology transfer or performance sharing between multiple parties means that public institutions provide support to the private sector so that it can take the lead and develop required technology. These instances can be good examples of public institutions serving as the foundation and creating social value by removing new technology entry barriers for small and medium-sized enterprises and supporting the development of the latest prioritized technology or product. Accordingly, there needs to be established a cooperative ecosystem between small, medium, and large companies in a win-win approach to increase the adoption rate of SME support projects and provide more technical advice in the road sector and thereby, to expand the cases of shared growth where outcomes are shared in the road sector.

As mobile shopping has increased in the new media age, fashion consumers’ decision making and product consumption processes have changed. The volume of consumer-driven information has expanded since media and social networking sites have enabled consumers to share information they obtain. The purpose of this study was to determine the factors affecting information searching strategies and information sharing about fashion products. An online survey collected data from 466 respondents, relating to the influence of product price level and consumer SNS commitment level on information search and information sharing. Experimental design of three product price level and two consumer SNS commitment level was used. Analysis of the data identified factors in fashion information searching as ongoing searching, prepurchase web portal information search, and prepurchase marketing information search. For low-price fashion products, prepurchase product-detail influenced intention to share information. For mid-priced products, ongoing search significantly affected intention to share information. Both ongoing search and prepurchase marketing information search showed significant effects for high-price products. Consumers who are more committed to SNS engaged in significantly more searching in all aspects of information search factors. Significant interaction effect was detected for consumer SNS commitment level and product price level. When consumers with low consumer SNS commitment search for information on lower-priced fashion products, they are less likely do a prepurchase web portal information search.

세계 작물보호제의 개발 흐름은 화학농약보다 친환경제제에 더욱 집중하고 있다. 이는, 수십 년 동안 행해진 화학농약 의존 농업에 대한 경각심의 우회적 표출이며, 개선하려는 국제적 움직임으로 해석할 수 있다. 친환경제제 중 하나인 곤충페로몬 이용 제품은 화학농약을 대체하거나 감소시킬 수 있는 제제로 국내외적으로 평가받고 있다. 이러한 곤충페로몬을 이용한 친환경 제품이 국내농업에 사용된 지 약 16년이 되었다. 그동안 국내 농업시장에서 통용된 곤충페로몬 이용 제품에는 어떠한 것이 있었고, 시기 및 지역별로 제품 사용의 변화 확인을 통해 다양성을 향한 앞으로의 제품 개발과 활용을 토의하고자 한다. 또한, 곤충페로몬 방출기 관련 연구개발 지식 공유를 통해, 제품 및 기술 개발을 위한 논의를 하고자 한다.

This article study the Letter of Collection(LOC) of U.S. National Cancer Institute(NCI) and the INBio-Merck Agreement as a international cases of the Access to Genetic Resources and Benefit- Sharing. These cases have the matching parts to the provisions of concern international norms. But, these cases not reflected the provisions of international norm because they concluded before 2010. So access to genetic resources and benefit sharing agreement will be concluded in the future must include the following contents. First, the provisions of the provider and the user of genetic resources as a parties of benefit sharing agreement. Second, the provisions of participation of stakeholders. Third, the provisions of prior informed consent. Prior informed consent must provide basic principles, elements, competent national authority granting and information of procedures for obtaining prior informed consent. Fourth, the provisions of mutually agreed terms. Fifth, the incentive measures could be used in the implementation for conservation and sustainable use of biodiversity, to promote accountability of access and benefit sharing, to provide for national monitoring and reporting.

The planetary gearing system is compact and lightweight. The performance of planetary gearing system which uses floating intermediate rings have been found to be very good for practical systems. To apply this system for the reduction of rotation of an engine, in designing stage, the quantitative estimate of the load sharing factors is required for understanding the performance. The method widely used for this purpose is to make use of elastic deformation of components of the structure or to utilize hydrodynamic oil film. This paper shows the way how to analyze the static load sharing factors by using the coefficient ''. This method can be applied for non-linear systems such as oil film bearing. The influences of various factors on '' of oil film spring are also shown. Furthermore, It is established in this study that the use of floating intermediate ring in designing the planetary gearing system has a very high reliability.

본 연구는 팀장의 임파워링 리더십이 팀 지식공유 및 팀 효능감에 미치는 영향과 함께 임파워링 리더십과 팀 효능감 간 관계에 있어 팀 지식공유의 매개효과를 살펴보고자 한다. 가설의 검증을 위해 광주·전남 지역의 17개 조직 79개 팀 229명의 종업원과 그들의 직속상사 79명을 대상으로 설문조사를 실시하였다. 연구 결과, 팀장의 임파워링 리더십은 팀 내 지식공유에 정(+)의 유의한 영향을 주는 것으로 나타났다. 이를 통해 조직 차원에서 팀 내 지식공유 활성화를 위해 임파워링 리더십 개발에 힘써야 함을 시사해 주고 있다. 또한, 팀 지식공유는 팀 효능감에 유의한 정(+)의 영향을 주는 것으로 나타났다. 마지막으로, 팀 내 지식공유는 팀장의 임파워링 리더십과 팀 효능감 간의 관계를 매개하고 있음을 발견하였다. 연구결과는 임파워링 리더십이 팀 효능감에 직접적인 영향을 주지는 않지만 팀 지식공유를 통해 간접적으로 영향을 주고 있음을 시사해 주고 있다. 연구결과를 토대로 연구의 한계 및 향후 연구방향을 제시하였다.