Search results

The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the Resource Description Framework (RDF). Alongside Named Graphs, this approach offers opportunities to leverage a meta-level for data modeling and data applications.

In this extended paper, the authors build onto three modeling use cases published in a previous paper: (1) provide provenance information, (2) maintain backwards compatibility for existing models, and (3) reduce the complexity of a data model. The authors present two scenarios where they implement the use of the meta-level to extend a data model with meta-information.

The authors present three abstract patterns for actively using the meta-level in data modeling. The authors showcase the implementation of the meta-level through two scenarios from our research project: (1) the authors introduce a workflow for triple annotation that uses the meta-level to enable users to comment on individual statements, such as for reporting errors or adding supplementary information. (2) The authors demonstrate how adding meta-information to a data model can accommodate highly specialized data while maintaining the simplicity of the underlying model.

Through the formulation of data modeling patterns with RDF-star and the demonstration of their application in two scenarios, the authors advocate for data modelers to embrace the meta-level.

With RDF-star being a very new extension to RDF, to the best of the authors’ knowledge, they are among the first to relate it to other meta-level approaches and demonstrate its application in real-world scenarios.

This study aims to understand how different levels of streamer channels influence luxury brand sales in live streaming commerce. This study also seeks to understand the conditions under which luxury brands may benefit more from different level streamer channels.

Panel data were collected from 17 international luxury brands on the Douyin live streaming platform in an 18 week period from August to December 2020 and analyzed by using a two-way fixed effects model.

The authors compared different mega-, macro- and micro-streamer channels within live streaming commerce and found that the densities of mega- and macro-streamer channels had significant positive impacts on luxury brand sales in live streaming commerce. Moreover, the effects of the density of streamer channel on luxury brand sales were moderated by such variables as product line breadth, product line depth, product type (star/non-star) and product price (high/low). The authors found that product line breadth and depth could reduce the positive impact of the densities of mega- and macro-streamer channels on luxury brand sales. For star products and high-priced products, the relationship between the density of mega-streamer channel and luxury brand sales was more likely to be observed than for non-star products and low-priced products. The relationship between the density of macro-streamer channel and luxury brand sales was more likely to be observed in low-priced products than in high-priced products.

The findings make important contributions to the literature in that the authors expand the influencer-brand fit theory by proposing a new model of effects of the densities of mega-, macro- and micro-streamer channels on sales performance across different luxury products to improve our understanding of the fit among influencers, brands and products. This helps luxury brands make basic decisions of “who sells” and “sells what” when engaging in live streaming commerce.

The aim of this study was to determine if there are asymmetries in the pass-through of West Texas Intermediate (WTI) crude oil prices to its derivatives (diesel and gasoline) in the Brazilian market.

Initially, the future WTI oil price series was analyzed using the self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) non-linear models. Subsequently, the threshold autoregressive error-correction model (TAR-ECM) and Markov-switching model were used.

The findings indicated high prices throughout 2008 due to the subprime crisis. The findings indicated high prices throughout 2008 due to the subprime crisis. The results indicated that there is long-term pass-through of oil prices in both methods, suggesting an equilibrium adjustment in the prices of diesel and gasoline in the analyzed period. Regarding the short term, the variations in contemporary crude oil prices have positive effects on the variations in fuel prices. Lastly, this behavior can partly be explained by the internal price management structure adopted during almost all of the analyzed period.

This paper contributes to the literature at some points. The first contribution is the modeling of the oil price series through non-linear models, further enriching the literature on the recent behavior of this time series. The second is the simultaneous use of the TAR-ECM and Markov-switching model to capture possible short- and long-term asymmetries in the pass-through of prices, as few studies have applied these methods to the future price of oil. The third and main contribution is the investigation of whether there are asymmetries in the transfer of oil prices to the price of derivatives in Brazil. So far, no work has investigated this issue, which is very relevant to the country.

The focus of this research is to investigate if user-generated content (UGC) generated in the Booking platform can support quality management improvement within the hospitality industry by increasing customer satisfaction and eliminating defects more efficiently. Hence, it contributes to understanding how data-driven companies can rely on customer data to focus on innovation and performance improvement to meet customer requirements, eliminate defects and increase customer satisfaction.

Following the literature review, information was collected from the digital platform Booking, encompassing 15 hotel industry companies in Portugal Porto and Braga regions, selected due to their high number of customer reviews. This data was organized and categorized, eliminating all unnecessary information for the research and building an Excel database. The database was subsequently analysed with SPSS and Voyant software, performing statistical analysis, hypothesis testing and text-mining techniques to analyse the comments. After these analyses, applying quality tools allowed for more in-depth conclusions.

The research results highlight that customers' most relevant requirements in the Portuguese hospitality industry are breakfast, parking and a swimming pool. It was also possible to realize that the location is an attractive requirement, the bathroom is a must-be requirement and breakfast is a performance requirement. The results also allowed us to answer the most critical research question: “Is user-generated content a valuable aid to quality?” the answer is yes since it was possible to use the data to find improvements and faults/failures in the services.

The results of this study represent an essential step towards a complete understanding of how to take advantage of UGC within the hospitality industry by establishing a solid base of techniques, methods and quality tools for UGC analysis that can be applied in future research on different industry sectors.

Organizational theorists and strategy scholars are both interested in how organizations deal with ambiguity, especially in relation to implementation. This chapter examines one source of ambiguity that organizations face, which is based on their efforts to implement moral mandates. These mandates, which are related to areas such as environmental sustainability and diversity, are inherently ambiguous, as they lack a shared understanding regarding their scope and associated practices. They are also often broad and systemic and may be unclearly aligned with an organization's strategy. Due to these challenges, in this chapter, we theorize that collective action at the field level is necessary for organizations to advance and concretize moral mandates. We examine this theorizing through the case of the implementation of sustainability in higher education. We hypothesize and find support for the idea that when an organization's members engage in collective action at the field level, those organizations have an increased likelihood of achieving sustainability implementation. To gain insight into this field-to-organization relationship, we qualitatively examine 18 years of conversations from an online forum to develop a process model of moral mandate implementation. We theorize that collective action functions as a field-configuring space, in which actors from a variety of organizations come together to (1) refine the scope of the mandate and (2) create an implementation repertoire that actors can draw on when seeking to bring sustainability to their own organizations. Overall, our study provides a model of how ambiguous moral mandates can be implemented by highlighting the important role of collective action across organizations in concretizing those mandates and providing actors with the tools for their implementation.

The purpose of this study is to propose and develop an antecedent model from star hotel employee viewpoint and a consequence model for star hotel customers’ evaluation of the brand equity development process.

In terms of the study setting, structural equation modelling was conducted. Study 1 used the views of 323 star hotels’ employees on the mutual relationships among employee-based brand equity, and Study 2 used 516 star hotels’ customer perspectives concerning the mutual relationships among customer-based brand equity.

In the antecedent model of Study 1 from an employee viewpoint, service quality is a foundational attribute of the indirect influences of brand equity development through brand promise, values and message. A moderating role of brand identity is also found. In the consequence model of Study 2 from the perspective of customers’ evaluation, mutual relationships of brand equity are identified, and social interactions are established that enhance the positive relationships among the different critical attributes of brand equity.

Although numerous hotel branding studies have identified the consequences of hotels for employees, few have simultaneously considered employees and customer feedback in terms of star hotel branding. This research considers the bidirectional effects of such a comprehensive perspective.

The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO₂ emissions during the time span from 1980 to 2020.

The study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in the Indian economy.

The estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO₂ emissions. The authors found that economic growth positively impacts CO₂ emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO₂ emissions. Similarly, RE consumption positively affects CO₂ emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO₂ emissions.

The study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO₂ emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO₂ emissions on further economic growth.

To the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in India, using the STAR model.

Studies have shown that higher education institutions (HEIs) need to achieve deep organizational learning to develop and implement long-term strategies for responding to the climate crisis. This study aims to analyze the sustainability efforts of HEIs, in particular those who use the sustainability tracking, assessment and rating system (STARS), to ascertain what type of organizational learning is being achieved.

This paper does this by analyzing perceptions of learning amongst this group of HEIs. More specifically, it analyzes survey data regarding perceptions of types and system levels of organizational learning achieved by 116 HEIs in the USA that currently use or have used STARS in the past. The approach also aims to develop a macro view of the relationships between practicing campus sustainability, using sustainability reporting tools and learning as an organization.

An examination of the practice of campus sustainability and its relationship to organizational learning reveals that the use of sustainability reporting promotes broad learning, but deep learning at the level of the organization is seldom achieved.

Given the success of using sustainability reporting tools to diffuse knowledge and foster broad learning, this paper argues that such tools should incorporate more metrics relative to soft organizational characteristics of HEIs to shift organizational cultures and foster deeper organizational learning.

This work constitutes one of the few studies analyzing empirical data on campus sustainability, sustainability reporting and organizational learning for a large number of HEIs.

Today, the increasing use of fossil fuels, energy security, concerns and the great importance of achieving sustainable economic growth underscore the urgent need to transition to a green energy system as soon as possible. To shed light on the relationship between the economy and renewable energy, this study assesses the nonlinear relationship between renewable energy consumption and economic growth for 24 OECD countries between 1990 and 2015.

The authors apply two nonlinear models: panel threshold regression (PTR) and panel smooth transition regression (PSTR).

The results show that the positive effect of renewable energy consumption on economic growth is conditional. On the one hand, the results of the nonlinear PTR model yielded a threshold value for renewable energy consumption of about 251.17. Below this threshold, the authors find a negative impact of renewable energy consumption on economic growth. However, above this threshold, renewable energy consumption becomes a favorable source of economic growth. Using the nonlinear PSTR model based on the gamma transition parameter of 2.014, the transition from low renewable energy consumption regime to higher is abrupt.

Referring to previous studies analyzing linear causality between renewable energy and economic growth, most of the results show various mixed and non-stable effects over the study period. The contributions of this study consist in conduct a series of empirical tests of the nonlinear effects of renewable energy use on economic growth using two nonlinear approaches such as the PTR and PSTR models. If the authors show that such a relationship is nonlinear, it is essential to check whether the transition from one weak regime to another strong regime is abrupt or smooth, using the PSTR approach.

This study aims to examine whether and how corporate sustainability capability influences energy efficiency through competitive intensity and slack resource availability.

The authors applied a two-wave research design and administered a survey questionnaire to senior-level managers of 78 ISO-14001 and ISO-50001 certified manufacturing companies. The authors use a multi-method approach for data analysis. AMOS 23 software was applied for covariance-based structural equation modeling. In addition, SPSS 25 software was applied for hierarchical regression analysis to examine the causal relationships in the model.

The finding reveals that corporate sustainability capabilities, which include energy-saving opportunities, seizing energy-saving opportunities and resource reconfiguration, significantly improve firms’ energy efficiency. In addition, competitive intensity and slack resource availability positively moderated the relationship between corporate sustainability capability and energy efficiency.

To the best of the authors’ knowledge, this study is the first to examine the link between corporate sustainability capability and energy efficiency in developing countries such as Pakistan. Although the influence of various corporate sustainability capabilities on sustainable performance has been widely examined in the literature, the role of corporate sustainability capability has been limitedly explored with energy efficiency. This study extends the literature by adding to the knowledge of corporate sustainability capability that enhances boundary conditions in developing countries.