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Smart tourism has become an inevitable trend in future tourism development. However, despite significant investment in its technological foundation, little is known about whether and when tourists are willing to be involved in smart tourism. This study explores tourists' willingness to contribute to smart tourism development by empirically examining their intention to share personal information and use smart technology.

Based on construal level theory (CLT), a 2 (far/near spatial distance) × 2 (gain/loss persuasive information frame) × 2 (altruistic/egoistic value orientation) laboratory experiment with different contextual features was designed to examine tourists' willingness to contribute to smart tourism.

Tourists are most willing to share personal information and use smart technologies when spatial distance aligns with information framing, spatial distance aligns with value orientation and information framing aligns with value orientation.

This study provides essential insights for destination management organizations (DMOs) about tourists' perceptions of smart tourism, enabling DMOs to develop more precise marketing strategies to encourage tourists to contribute to smart tourism development and enrich tourists' travel experiences.

This study enriches theoretical knowledge of DMOs' boundaries in encouraging tourists to contribute to smart tourism and provides critical insights into future smart tourism development for researchers and practitioners.

Between 1985 and 2000, the six largest US pharmaceutical firms entered a very active period of partnerships with other pharmaceutical firms to expand their knowledge of biotechnology-based research and development (R&D) frameworks and to bolster the growth of their drug portfolios. The purpose of this study is to examine the annual reports published by these companies for evidence of strategic framing of these partnerships.

A content analysis method was most appropriate for this study, as it allows for analysis of a large amount of information and accurate analysis over time. Ninety-six annual reports from the six major US pharmaceutical firms (Abbott, Bristol Myers Squibb, Eli Lilly, Johnson and Johnson, Merck, and Pfizer) were coded. The final codebook included 18 categories derived from framing theory. After collection, the data were uploaded to SPSS for statistical analysis.

Results indicate that mention of partnerships grew considerably in depth and length over time, but companies did not consistently employ frames to describe why or how they engaged in external partnerships.

This is the first study to assess mentions of pharmaceutical firms' external efforts to build their R&D programs and drug portfolios, from the intersecting perspectives of framing theory and the resource-based view (RBV) of the firm, to illustrate how changes were communicated to shareholders during a dynamic period of change within the industry.

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

The lean startup approach (LSA) is extensively utilized by early-stage entrepreneurs, with “pivot” serving as a key pillar. However, there is a research gap concerning the boundary conditions impacting LSA and pivot decisions, especially when addressing societal challenges, as in the context of transformational entrepreneurship. In this regard, the healthcare sector, further compounded by a lack of research on startups and scale-ups, presents an embraced opportunity to provide multiple contributions for both theory and practice.

The present investigation employs a grounded approach to explore the experiences of the co-founders of a fast-growing Italian e-health startup. A narrative strategy was employed to organize conditions and evolving strategic action/interactions into three different pivoting phases of the startup – before the pivot, its enactment and aftermath – with primary and secondary data collected over a period of one year.

Pivoting in digital healthcare unfolded as a liminal experience marked by factors such as high regulation, multiple stakeholders, technological and symbolic ambivalence, resource-intensive demands and institutional actors acting as pathway pioneers, leading to an information overload and unforeseeable uncertainty to manage. These factors challenge entrepreneurs' ability to attain optimal distinctiveness, presenting the paradoxical need for vertical flexibility for scaling up.

By uniquely illuminating the sector’s constraints on entrepreneurial phenomena, this study provides a valuable guide for entrepreneurs and institutional actors in addressing societal challenges.

This study introduces a process model of transformational information crafting when pivoting, highlighting the role of entrepreneurs' transformational stance and platform-mediated solutions as engines behind strategies involving information breaking and transition, preceding knowledge-driven integration strategies.

This interdisciplinary study aims to analyze how service organizations communicate sustainable beliefs in their social media narratives and use them to generate brand awareness, customer recognition and ongoing demand for sustainable service.

A two-phase exploratory analysis of 10,342 tweets from 2019–2020 was conducted by sustainable global corporations to identify best practices for their social media teams operating within a service-based business model. First, the significant themes were identified using an unguided machine learning approach of three types of firms: services, goods and mixed. Next, the full set of tweets with linguistic sentiment analysis was analyzed followed by a deeper view of the services-based organizations based on their strategic focus (business-to-business [B2B] versus mixed).

The findings indicate that tweets that appear to create the highest customer engagement are characterized as having high levels of analytical language, high clout (i.e. are socially relevant), a positive tone, a high number of words and a high number of words per sentence. On the other hand, having complex language in terms of six-letter words does not seem to associate with customer engagement. The last level of analysis shows that B2B services-based corporations with positive tone and higher word count exhibit higher levels of retweets. Implications include providing rational and informational tweets to increase engagement and highlight societal relevance.

Climate change has negative consequences on human and physical capital, and ecosystems across the globe. This study provides specific recommendations for how services corporations can increase their sustainable communications and actions.

The key implication of our research is that corporations must strategically design social media narratives about climate change as part of their online branding and communications process.

This pan-Canadian study examines the information practices of STEM-trained immigrant women to Canada as they navigate workfinding and workplace integration. Our study focuses on a population of highly skilled immigrant women from across Canada and uses an information practice lens to examine their lived experiences of migration and labour market integration. As highly trained STEM professionals in pursuit of employment, our participants have specific needs and challenges, and as we explore these, we consider the intersection of their information practices with government policies, settlement services and the hiring practices of STEM employers.

We conducted a qualitative study using in-depth interviews with 74 immigrant women across 13 Canadian provinces and territories to understand the nature of their engagement with employment-seeking in STEM sectors. This article reports the findings related to the settlement and information experiences of the immigrant women as they navigate new information landscapes.

As immigrants, as women and as STEM professionals, the experiences of the 74 participants reflect both marginality and privilege. The reality of their intersectional identities is that these women may not be well-served by broader settlement resources targeting newcomers, but neither are the specific conventions of networking and job-seeking in the STEM sectors in Canada fully apparent or accessible to them. The findings also point to the broader systemic and contextual factors that participants have to navigate and that shape in a major way their workfinding journeys.

The findings of this pan-Canadian study have theoretical and practical implications for policy and research. Through interviews with these STEM professionals, we highlight the barriers and challenges of an under-studied category of migrants (the highly skilled and “desirable” type of immigrants). We provide a critical discussion of their settlement experiences and expose the idiosyncrasies of a system that claims to value skilled talent while structurally making it very difficult to deliver on its promises to recruit and retain highly qualified personnel. Our findings point to specific aspects of these skilled professionals’ experiences, as well as the broader systemic and contextual factors that shape their workfinding journey.

This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.

This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.

Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.

Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.

This study examines the interplay between media-induced emotional crisis framing (anger vs sadness) and message sidedness of crisis response on publics’ attribution of crisis responsibility as well as subsequent company evaluation and supportive behavioral intention.

A 2 (emotion: anger vs sadness) x 2 (crisis response: one-sided vs two-sided) online experiment was conducted among 161 participants in the USA.

Results showed that anger-inducing media framing of the crisis elicited higher levels of crisis responsibility attribution and more negative company evaluation, compared with sadness-inducing media framing. One-sided message response was more effective than two-sided message response in lowering attribution of crisis responsibility when sadness was induced, but no difference was found under the anger-induced condition. Attribution of crisis responsibility fully mediated the effects of emotional crisis framing on company evaluation and supportive behavioral intention toward the company.

This study is among the first to examine the interaction effect between emotional media framing and response message sidedness in an ambiguous crisis. Drawing on the interdisciplinary theoretical frameworks, this study integrates the situational crisis communication theory, appraisal-tendency framework and message sidedness in persuasion literature. As such, it contributes to theoretical development in crisis communication and offers communication managers guidance on how to effectively address emotionally framed crises.

Addressing the significant differences between referral programs and traditional promotional marketing, this paper aims to investigate and examine the impact of how reward-related information is presented within referral programs and how it interacts with reward size and reward allocation.

This study adopts framing effect and equity theory to build the relationship between reward presentation, reward size and reward allocation. Then, two scenario-based experimental studies are designed and conducted on Amazon Mechanical Turk.

The results show that there is no direct impact of reward presentation on referral likelihood, while the effect relies on reward size. As the levels of reward size increase, the referral likelihood gradually shifts from percentage form to dollar form as perceived size mediates the interaction effect on referral likelihood. Further, adding information about reward allocation also indicate the different impacts of equity and inequity on influencing the above findings.

The study contributes to the literature by introducing reward presentation and emphasizes its impact on individual’s behavior decisions in the context of referral programs. This study extends and broadens the scope and effectiveness of the framing effect on traditional promotional marketing strategies, while also bridging the gap in the literature by examining the combined role of information about rewards.

This paper examines the framing of digital transformation. The research questions are specified as follows: what are the different types of framing strategies in response to digital transformation? How do the strategies differ across organizations? Theoretically, the authors draw on the framing perspective to emphasize the use of linguistic frames in shaping innovation and change processes. Empirically, the authors choose to study the Taiwanese sectors, including publicly governed entities, traditional private business or technology-based ventures.

The authors’ approach combines topic modeling and qualitative analysis. Using data collected from newspaper and magazine articles, the authors employ topic modeling to generate a set of distinctive framings that Taiwanese actors typically adopt to motivate and justify their digital move. The authors also conduct personal interviews to qualitatively complement the authors’ topic modeling analysis and to identify the rationale behind the linguistic framings and the strategic differences brought about by the various organizations.

The authors identify five topics that the Taiwanese actors commonly used in the framing of digital transformation. These topics or frames are labeled as cross-domain coordination, market demand, intelligent technology, global trend and competition and digital innovation. The practical use of the framings is contingent on organizational characteristics. Furthermore, the authors show how the framings can be classified as either positive framing (e.g. winning the next war) or negative framing (e.g. innovate or die), generally applicable to organizations around the world struggling to cope with digital disruption.

The authors’ study has two research implications. First, the authors extend the appreciation of the digital transformation from the usual concern with technological and business model innovations to linguistic or framing practices. Second, the authors enrich the framing analysis by emphasizing a practice or contingency perspective based on sector difference. The findings are subject to the limitations of the choice of only established and reputable media outlets, the diatextual reading and filtering of useful articles for topic modeling analysis and the use of world frequency to account for frame significance.

The authors shift actors' attention from improving technical efficiency to acquiring linguistic resources in the pursuit of digitalization. For example, framing the digital transformation in terms of creating a market orientation calls for not only real consumer power but also strategic discursive competence that enables the move to change. The findings also point out that practitioners can enlarge the scope of their agency rather than being trapped in the habituated routine of practices. Despite social embeddedness, organizations are more often widely connected and built enough to call for more of the cognitive frames to appeal to heterogeneous stakeholders.

The authors study contributes to the literature by developing a linguistic or socio-cognitive view of digital transformation strategy that is capable of expanding organizational attention toward change and innovation. The authors explore menus of strategic frames employed by actors in response to digital transformation. We also address the application of a machine-learning tool such as topic modeling to explore the socio-cognitive dimensions of digital transformation. Furthermore, the analysis leads us to identify the outcomes or effects – either positive or negative – that move beyond the particular Taiwanese case to explain the framing of digital transformation in general.